BACKGROUND Stress ulcers are common complications in critically ill patients,with a higher incidence observed in older patients following gastrointestinal surgery.This study aimed to develop and evaluate the effective...BACKGROUND Stress ulcers are common complications in critically ill patients,with a higher incidence observed in older patients following gastrointestinal surgery.This study aimed to develop and evaluate the effectiveness of a multi-modal intervention protocol to prevent stress ulcers in this high-risk population.AIM To assess the impact of a multi-modal intervention on preventing stress ulcers in older intensive care unit(ICU)patients postoperatively.METHODS A randomized controlled trial involving critically ill patients(aged≥65 years)admitted to the ICU after gastrointestinal surgery was conducted.Patients were randomly assigned to either the intervention group,which received a multimodal stress ulcer prevention protocol,or the control group,which received standard care.The primary outcome measure was the incidence of stress ulcers.The secondary outcomes included ulcer healing time,complication rates,and length of hospital stay.RESULTS A total of 200 patients(100 in each group)were included in this study.The intervention group exhibited a significantly lower incidence of stress ulcers than the control group(15%vs 30%,P<0.01).Additionally,the intervention group demonstrated shorter ulcer healing times(mean 5.2 vs 7.8 days,P<0.05),lower complication rates(10%vs 22%,P<0.05),and reduced length of hospital stay(mean 12.3 vs 15.7 days,P<0.05).CONCLUSION This multi-modal intervention protocol significantly reduced the incidence of stress ulcers and improved clinical outcomes in critically ill older patients after gastrointestinal surgery.This comprehensive approach may provide a valuable strategy for managing high-risk populations in intensive care settings.展开更多
BACKGROUND Approximately 30%of patients with head and neck cancer experience adverse effects caused by anxiety and depression.Considering the high prevalence,implementing customized interventions to ease adverse emoti...BACKGROUND Approximately 30%of patients with head and neck cancer experience adverse effects caused by anxiety and depression.Considering the high prevalence,implementing customized interventions to ease adverse emotional states is imperative.AIM To evaluate the efficacy of cognitive behavioral therapy(CBT)-based psychological interventions in improving the psychological well-being and quality of life(QoL)of patients with laryngeal carcinoma.METHODS This study enrolled 120 patients admitted from February 2022 to February 2024.The control group,comprising 50 participants,received standard supportive psychological care,while the research group,consisting 70 participants,underwent CBT-based interventions.Several clinical outcomes were systematically assessed that included postoperative recovery metrics(duration of tracheostomy and nasogastric tube dependence and length of hospitalization),psychological status(Self-Rating Anxiety Scale and Self-Rating Depression Scale),nutritional markers(serum albumin and hemoglobin levels),sleep quality(Self-Rating Scale of Sleep and Athens Insomnia Scale),and QoL(Functional Assessment of Cancer Therapy-Head and Neck).RESULTS The results demonstrated that the research group experienced superior outcomes,with significantly reduced durations of tracheostomy and nasogastric tube dependence,as well as shorter hospital stays,compared with the control group.Additionally,the research group exhibited markedly lower post-intervention Self-Rating Anxiety Scale,Self-Rating Depression Scale,Self-Rating Scale of Sleep,and Athens Insomnia Scale scores,along with minimal but higher change in serum albumin and hemoglobin levels compared with the control group.All five domains of Functional Assessment of Cancer Therapy-Head and Neck showed notable improvements in the research group,exceeding those observed in the control group.CONCLUSION CBT-based psychological support positively affects the mental well-being and QoL of patients with laryngeal carcinoma,highlighting its potential for broader clinical application.展开更多
Microglia are the resident macrophages of the central nervous system.They act as the first line of defense against pathogens and play essential roles in neuroinflammation and tissue repair after brain insult or in neu...Microglia are the resident macrophages of the central nervous system.They act as the first line of defense against pathogens and play essential roles in neuroinflammation and tissue repair after brain insult or in neurodegenerative and demyelinating diseases(Borst et al.,2021).Together with infiltrating monocyte-derived macrophages,microglia also play a critical role for brain tumor development,since immunosuppressive interactions between tumor cells and tumor-associated microglia and macrophages(TAM)are linked to malignant progression.This mechanism is of particular relevance in glioblastoma(GB),the deadliest form of brain cancer with a median overall survival of less than 15 months(Khan et al.,2023).Therefore,targeting microglia and macrophage activation is a promising strategy for therapeutic interference in brain disease.展开更多
The intersection of visual impairment and mental health has profound effects on quality of life and warrants attention from healthcare providers,educators,and policymakers.With 20 million children under the age of 14 ...The intersection of visual impairment and mental health has profound effects on quality of life and warrants attention from healthcare providers,educators,and policymakers.With 20 million children under the age of 14 affected globally,older adults also experience significant psychological impact including depression,anxiety,and cognitive impairment.The implications of vision-related challenges extend far beyond mere sight.Depression and anxiety,exacerbated by social isolation and reduced physical activity,underscore the need for comprehensive interventions that address both medical and psychosocial dimensions.By recognizing the profound impact of ocular morbidities like strabismus,myopia,glaucoma,and age-related macular degeneration on mental health and investing in effective treatments and inclusive practices,society can pave the way for a healthier,more equitable future for affected individuals.There is evidence that myopic children experience a higher prevalence of depressive symptoms compared to their normal peers,and interventions like the correction of strabismus can enhance psychological outcome-demonstrating the value of an integrated management approach.展开更多
Objective To develop a non-invasive predictive model for coronary artery stenosis severity based on adaptive multi-modal integration of traditional Chinese and western medicine data.Methods Clinical indicators,echocar...Objective To develop a non-invasive predictive model for coronary artery stenosis severity based on adaptive multi-modal integration of traditional Chinese and western medicine data.Methods Clinical indicators,echocardiographic data,traditional Chinese medicine(TCM)tongue manifestations,and facial features were collected from patients who underwent coro-nary computed tomography angiography(CTA)in the Cardiac Care Unit(CCU)of Shanghai Tenth People's Hospital between May 1,2023 and May 1,2024.An adaptive weighted multi-modal data fusion(AWMDF)model based on deep learning was constructed to predict the severity of coronary artery stenosis.The model was evaluated using metrics including accura-cy,precision,recall,F1 score,and the area under the receiver operating characteristic(ROC)curve(AUC).Further performance assessment was conducted through comparisons with six ensemble machine learning methods,data ablation,model component ablation,and various decision-level fusion strategies.Results A total of 158 patients were included in the study.The AWMDF model achieved ex-cellent predictive performance(AUC=0.973,accuracy=0.937,precision=0.937,recall=0.929,and F1 score=0.933).Compared with model ablation,data ablation experiments,and various traditional machine learning models,the AWMDF model demonstrated superior per-formance.Moreover,the adaptive weighting strategy outperformed alternative approaches,including simple weighting,averaging,voting,and fixed-weight schemes.Conclusion The AWMDF model demonstrates potential clinical value in the non-invasive prediction of coronary artery disease and could serve as a tool for clinical decision support.展开更多
Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single ...Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single target”presents significant challenges due to its holistic approach.Network pharmacology and its core theory of network targets connect drugs and diseases from a holistic and systematic perspective based on biological networks,overcoming the limitations of reductionist research models and showing considerable value in TCM research.Recent integration of network target computational and experimental methods with artificial intelligence(AI)and multi-modal multi-omics technologies has substantially enhanced network pharmacology methodology.The advancement in computational and experimental techniques provides complementary support for network target theory in decoding TCM principles.This review,centered on network targets,examines the progress of network target methods combined with AI in predicting disease molecular mechanisms and drug-target relationships,alongside the application of multi-modal multi-omics technologies in analyzing TCM formulae,syndromes,and toxicity.Looking forward,network target theory is expected to incorporate emerging technologies while developing novel approaches aligned with its unique characteristics,potentially leading to significant breakthroughs in TCM research and advancing scientific understanding and innovation in TCM.展开更多
Objective:To evaluate the value of rehabilitation nursing based on mind mapping model combined with psychological intervention for patients with nephrotic syndrome(NS).Methods:A total of 60 patients with NS who visite...Objective:To evaluate the value of rehabilitation nursing based on mind mapping model combined with psychological intervention for patients with nephrotic syndrome(NS).Methods:A total of 60 patients with NS who visited our hospital from January 2024 to December 2024 were selected as samples and randomly divided into groups.The observation group received rehabilitation nursing based on the mind mapping model combined with psychological intervention,while the control group received routine intervention.The differences in emotional scores,self-care ability scores,compliance,and complications were compared between the two groups.Results:The anxiety(SAS)and depression(SDS)scores of the observation group were lower than those of the control group,while the self-care ability scale(ESCA)score was higher than that of the control group(P<0.05).The compliance rate of the observation group was higher than that of the control group(P<0.05).The complication rate of NS in the observation group was lower than that in the control group(P<0.05).Conclusion:Rehabilitation nursing based on the mind mapping model combined with psychological intervention can enhance self-care ability,reduce negative emotions,and reduce complications in NS nursing,which is efficient and feasible.展开更多
With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intellig...With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intelligent SA(ISA).However,the existing AI-based SA approaches often rely on unimodal data and lack a comprehensive description and benchmark of the ISA tasks utilizing multi-modal data for real-time ATC environments.To address this gap,by analyzing the situation awareness procedure of the ATCOs,the ISA task is refined to the processing of the two primary elements,i.e.,spoken instructions and flight trajectories.Subsequently,the ISA is further formulated into Controlling Intent Understanding(CIU)and Flight Trajectory Prediction(FTP)tasks.For the CIU task,an innovative automatic speech recognition and understanding framework is designed to extract the controlling intent from unstructured and continuous ATC communications.For the FTP task,the single-and multi-horizon FTP approaches are investigated to support the high-precision prediction of the situation evolution.A total of 32 unimodal/multi-modal advanced methods with extensive evaluation metrics are introduced to conduct the benchmarks on the real-world multi-modal ATC situation dataset.Experimental results demonstrate the effectiveness of AI-based techniques in enhancing ISA for the ATC environment.展开更多
Background:Parenting exerts a profound influence on children’s mental health and behavioral development.Despite the high prevalence of children’s emotional and behavioral problems(CEBP)in China,evidence-based parent...Background:Parenting exerts a profound influence on children’s mental health and behavioral development.Despite the high prevalence of children’s emotional and behavioral problems(CEBP)in China,evidence-based parenting interventions remain scarcely investigated as preventive public health strategies.This pilot study evaluated a school-based intervention for preventing CEBP.Methods:We employed a quasi-experimental design with propensity score matching(PSM)to select 28 families(intervention:n=13;control:n=15)from two matched urban primary schools.Quantitative data from seven validated scales were analyzed using t-tests and ANCOVA.Qualitative insights were derived from 10 semi-structured interviews via thematic analysis.Results:Compared to the control group,the intervention group demonstrated significantly greater improvements in CEBP(p=0.020,Cohen’s d=0.92),parental adjustment(p=0.031,Cohen’s d=0.80),parenting confidence(p=0.003,Cohen’s d=1.04),and parentchild relationships(p=0.001,Cohen’s d=1.46).Non-significant effects were observed for parenting style,parental relationship,and parenting conflict(p>0.05).Qualitative analysis corroborated these findings and further identified contributing factors for non-significant outcomes,including challengeswithmeasurement adaptability and inconsistent co-parenting practices.Conclusions:This pilot study suggests that an authoritative parenting style may be effective and culturally adaptable in China.Positive parenting interventions appear to mitigate CEBP by reducing risk factors and enhancing protective factors.However,improving parental relationships and parenting conflict may require targeted strategies.Given the pilot nature of this PSM-matched study(n=28),the findings should be interpreted as exploratory and used primarily for intervention refinement.展开更多
BACKGROUND The development of hepatocellular carcinoma(HCC)is influenced by multiple factors.Interventional therapy offers an effective treatment option for patients with unresectable intermediate-to-advanced HCC.Inte...BACKGROUND The development of hepatocellular carcinoma(HCC)is influenced by multiple factors.Interventional therapy offers an effective treatment option for patients with unresectable intermediate-to-advanced HCC.Interventional therapy can induce electrocardiographic(ECG)abnormalities that may be associated with liver dysfunction,electrolyte disorders,and cardiac injury.AIM To explore the ECG alterations and determinants following interventional therapy in patients with HCC.METHODS Sixty patients undergoing interventional treatment for liver cancer were selected as study participants.According to the results of the dynamic ECG examination 1 day after surgery,the patients were divided into an abnormal group(n=21)and a nonabnormal group(n=39).With the help of dynamic ECG examination,the ECG parameters were compared and the baseline data of patients was recorded in the two groups.RESULTS The 24 hours QT interval variability,24 hours normal atrial polarization to ventricular polarization(R-R)interval(standard deviation),24 hours consecutive 5 minutes normal R-R interval,and 24 hours continuous 5 minutes normal R-R interval(standard deviation mean)were lower than patients in the nonabnormal group(P<0.05).The logistic analysis showed that age>60 years,liver function grade B,and postoperative body temperature 38°C were risk factors for abnormal dynamic electrocardiogram in patients with liver cancer intervention(P<0.05).CONCLUSION Interventional therapy for HCC can lead to ECG abnormalities,underscoring the clinical need for enhanced cardiac monitoring to mitigate myocardial complications.展开更多
BACKGROUND Simultaneous acute ischemic stroke(AIS)and myocardial infarction(cardio-cerebral ischemic attack)have rarely been reported in the literature.Currently,no clear evidence-based guidelines or clinical trials e...BACKGROUND Simultaneous acute ischemic stroke(AIS)and myocardial infarction(cardio-cerebral ischemic attack)have rarely been reported in the literature.Currently,no clear evidence-based guidelines or clinical trials exist to determine the optimal therapeutic strategy for these patients.CASE SUMMARY We present the case of a 27-year-old Chinese man who simultaneously experie-nced acute concomitant cerebrocardiac infarction(CCI)and painless ST-elevation myocardial infarction.The patient was successfully treated with elective percu-taneous coronary intervention(PCI)after receiving urgent systemic thrombolysis at the standard dose for AIS.CONCLUSION Urgent thrombolysis followed by elective PCI was an appropriate strategy for the management of simultaneous CCI.展开更多
A personalized outfit recommendation has emerged as a hot research topic in the fashion domain.However,existing recommendations do not fully exploit user style preferences.Typically,users prefer particular styles such...A personalized outfit recommendation has emerged as a hot research topic in the fashion domain.However,existing recommendations do not fully exploit user style preferences.Typically,users prefer particular styles such as casual and athletic styles,and consider attributes like color and texture when selecting outfits.To achieve personalized outfit recommendations in line with user style preferences,this paper proposes a personal style guided outfit recommendation with multi-modal fashion compatibility modeling,termed as PSGNet.Firstly,a style classifier is designed to categorize fashion images of various clothing types and attributes into distinct style categories.Secondly,a personal style prediction module extracts user style preferences by analyzing historical data.Then,to address the limitations of single-modal representations and enhance fashion compatibility,both fashion images and text data are leveraged to extract multi-modal features.Finally,PSGNet integrates these components through Bayesian personalized ranking(BPR)to unify the personal style and fashion compatibility,where the former is used as personal style features and guides the output of the personalized outfit recommendation tailored to the target user.Extensive experiments on large-scale datasets demonstrate that the proposed model is efficient on the personalized outfit recommendation.展开更多
Liver transplantation,as an effective therapy for patients with liver cancer,plays an important role in improving the quality of life of patients.However,the com-plexity and trauma of liver transplantation can easily ...Liver transplantation,as an effective therapy for patients with liver cancer,plays an important role in improving the quality of life of patients.However,the com-plexity and trauma of liver transplantation can easily lead to the occurrence of malnutrition in patients,and then increase the risk of postoperative complica-tions,which has aroused widespread clinical attention.Reasonable nutritional support can not only maintain the stability of the body’s internal environment,reduce the occurrence of complications,but also promote the recovery of liver and other organ functions.In recent years,with the in-depth understanding of nut-ritional metabolism after liver transplantation,the application of enteral nutrition and parenteral nutrition in nutritional support after liver transplantation has been increasingly extensive and achieved remarkable results.This paper discusses the effect of early postoperative nutritional intervention on patients with liver cancer and liver transplantation,and combined with its mechanism of action,can better understand the effectiveness of intervention,and provide reference for the deve-lopment of scientific and reasonable nutritional support programs in clinical pra-ctice.展开更多
This study aims to explore the characteristics of novice teachers’inappropriate behaviors in classroom teaching and their intervention strategies.With the continuous improvement of education quality,novice teachers f...This study aims to explore the characteristics of novice teachers’inappropriate behaviors in classroom teaching and their intervention strategies.With the continuous improvement of education quality,novice teachers face increasing challenges in teaching practice.Their inappropriate behaviors not only affect the classroom atmosphere but may also negatively impact students’learning outcomes.Therefore,researching the characteristics of novice teachers’inappropriate behaviors and their intervention strategies holds significant scientific and social value.This study employs a combination of quantitative and qualitative methods to analyze the behavioral patterns of novice teachers in classroom teaching and proposes corresponding intervention strategies.The results indicate that novice teachers’inappropriate behaviors mainly manifest as poor classroom management,monotonous teaching methods,and insufficient interaction with students.Based on these findings,the study proposes a series of effective intervention strategies,including enhancing teacher training,optimizing teaching design,and promoting positive interactions between teachers and students.The conclusions of the study not only provide practical guidance for educational practice but also point out directions for future research,emphasizing the crucial role of teacher professional development in improving teaching quality.展开更多
Non-communicable diseases (NCDs) are on the rise worldwide and in developing countries like Botswana. Unhealthy eating habits and lack of proper nutrition knowledge cause non-communicable diseases and affect adolescen...Non-communicable diseases (NCDs) are on the rise worldwide and in developing countries like Botswana. Unhealthy eating habits and lack of proper nutrition knowledge cause non-communicable diseases and affect adolescents. It is in adolescence that eating habits are formed that persist till adulthood. Lifestyle interventions are needed to curb NCDs in adolescents. This paper reports the findings of a study that aimed to validate a lifestyle intervention program and its effect on food intake, physical activity, and nutrition knowledge. It was a clustered randomized control trial study conducted in four (4) junior secondary schools. There were 46 participants, 21 in the control and 25 in the intervention arm, who were blindly assigned to each arm by a statistician. Information and skills on nutrition were imparted using the Information, Motivation, and Behavioral Skills model. The program was implemented for eight (8) weeks hourly after school. A questionnaire was used to collect data pre- and post-intervention. Number, proportion, percentage, and independent t-test (mean and SD or median and IQR, p-value) were calculated using numerical and categorical data. The findings showed that the lifestyle intervention was valid, and there was a slight decrease in the intake of sweets among participants in both trial arms (p = 0.066). There was no significant difference in terms of food intake. Only a small number of participants still ate a few fruits, and there was no change in vegetable intake in both trial arms (p = 0.641). There was no change in the intake of fried foods in both trail arms (p = 0.402). Regarding nutrition knowledge, there was a slight significant difference of p = 0.079 between the trial arms. Though the effect of the lifestyle intervention program was not statistically significant, the results are promising, especially if the duration could be increased to a longer period and a larger sample size included.展开更多
Multi-modal Named Entity Recognition(MNER)aims to better identify meaningful textual entities by integrating information from images.Previous work has focused on extracting visual semantics at a fine-grained level,or ...Multi-modal Named Entity Recognition(MNER)aims to better identify meaningful textual entities by integrating information from images.Previous work has focused on extracting visual semantics at a fine-grained level,or obtaining entity related external knowledge from knowledge bases or Large Language Models(LLMs).However,these approaches ignore the poor semantic correlation between visual and textual modalities in MNER datasets and do not explore different multi-modal fusion approaches.In this paper,we present MMAVK,a multi-modal named entity recognition model with auxiliary visual knowledge and word-level fusion,which aims to leverage the Multi-modal Large Language Model(MLLM)as an implicit knowledge base.It also extracts vision-based auxiliary knowledge from the image formore accurate and effective recognition.Specifically,we propose vision-based auxiliary knowledge generation,which guides the MLLM to extract external knowledge exclusively derived from images to aid entity recognition by designing target-specific prompts,thus avoiding redundant recognition and cognitive confusion caused by the simultaneous processing of image-text pairs.Furthermore,we employ a word-level multi-modal fusion mechanism to fuse the extracted external knowledge with each word-embedding embedded from the transformerbased encoder.Extensive experimental results demonstrate that MMAVK outperforms or equals the state-of-the-art methods on the two classical MNER datasets,even when the largemodels employed have significantly fewer parameters than other baselines.展开更多
Multi-modal knowledge graph completion(MMKGC)aims to complete missing entities or relations in multi-modal knowledge graphs,thereby discovering more previously unknown triples.Due to the continuous growth of data and ...Multi-modal knowledge graph completion(MMKGC)aims to complete missing entities or relations in multi-modal knowledge graphs,thereby discovering more previously unknown triples.Due to the continuous growth of data and knowledge and the limitations of data sources,the visual knowledge within the knowledge graphs is generally of low quality,and some entities suffer from the issue of missing visual modality.Nevertheless,previous studies of MMKGC have primarily focused on how to facilitate modality interaction and fusion while neglecting the problems of low modality quality and modality missing.In this case,mainstream MMKGC models only use pre-trained visual encoders to extract features and transfer the semantic information to the joint embeddings through modal fusion,which inevitably suffers from problems such as error propagation and increased uncertainty.To address these problems,we propose a Multi-modal knowledge graph Completion model based on Super-resolution and Detailed Description Generation(MMCSD).Specifically,we leverage a pre-trained residual network to enhance the resolution and improve the quality of the visual modality.Moreover,we design multi-level visual semantic extraction and entity description generation,thereby further extracting entity semantics from structural triples and visual images.Meanwhile,we train a variational multi-modal auto-encoder and utilize a pre-trained multi-modal language model to complement the missing visual features.We conducted experiments on FB15K-237 and DB13K,and the results showed that MMCSD can effectively perform MMKGC and achieve state-of-the-art performance.展开更多
BACKGROUND Excessive noise in healthcare environments—commonly described as"unwanted sound"—has been linked to a range of negative impacts on both patients and staff.In clinical settings,elevated noise lev...BACKGROUND Excessive noise in healthcare environments—commonly described as"unwanted sound"—has been linked to a range of negative impacts on both patients and staff.In clinical settings,elevated noise levels have been associated with sleep disruption,heightened cardiovascular stress,and an increased risk of delirium in patients.Among healthcare workers,noise can impair focus and cognitive performance,potentially compromising care quality.AIM To evaluate the effectiveness of educational and behavioural interventions in reducing noise levels within intensive care units(ICUs),recognizing their potential impact on patient outcomes and healthcare effectiveness.METHODS A prospective interventional study in two Singaporean teaching hospitals compared peak and average sound levels between control and intervention groups.An educational and behavioural intervention comprising talks,posters,and self-audits by nurse champions was initiated in two ICUs in one hospital on November 18,2023.Sound measurements were collected at 4 Locations within each ICU before and after intervention.Baseline measurements were taken from October 22,2023 to October 29,2023,and post-intervention measurements from December 21,2023 to December 22,2023.The hospitals served as the primary exposure variable,controlled for ICU type(medical vs surgical)and hour of the day.RESULTS Our analysis generated 48 pairs of peak and average sound level readings for each unit(control n=48 readings;intervention n=48 readings).The effect of the intervention was associated with a significant 4.8 dB decrease in average sound level(P=0.009)and a nonsignificant 4.3 dB decrease in peak sound level(P=0.104),adjusted for hour of day and type of ICU.CONCLUSION Educational and behavioural interventions successfully reduced average sound levels,emphasizing their positive impact on noise control.These findings contribute valuable insights for optimizing noise reduction efforts in critical care settings.Future studies may explore additional systemic and environmental interventions to enhance noise management strategies.展开更多
Integrating multiple medical imaging techniques,including Magnetic Resonance Imaging(MRI),Computed Tomography,Positron Emission Tomography(PET),and ultrasound,provides a comprehensive view of the patient health status...Integrating multiple medical imaging techniques,including Magnetic Resonance Imaging(MRI),Computed Tomography,Positron Emission Tomography(PET),and ultrasound,provides a comprehensive view of the patient health status.Each of these methods contributes unique diagnostic insights,enhancing the overall assessment of patient condition.Nevertheless,the amalgamation of data from multiple modalities presents difficulties due to disparities in resolution,data collection methods,and noise levels.While traditional models like Convolutional Neural Networks(CNNs)excel in single-modality tasks,they struggle to handle multi-modal complexities,lacking the capacity to model global relationships.This research presents a novel approach for examining multi-modal medical imagery using a transformer-based system.The framework employs self-attention and cross-attention mechanisms to synchronize and integrate features across various modalities.Additionally,it shows resilience to variations in noise and image quality,making it adaptable for real-time clinical use.To address the computational hurdles linked to transformer models,particularly in real-time clinical applications in resource-constrained environments,several optimization techniques have been integrated to boost scalability and efficiency.Initially,a streamlined transformer architecture was adopted to minimize the computational load while maintaining model effectiveness.Methods such as model pruning,quantization,and knowledge distillation have been applied to reduce the parameter count and enhance the inference speed.Furthermore,efficient attention mechanisms such as linear or sparse attention were employed to alleviate the substantial memory and processing requirements of traditional self-attention operations.For further deployment optimization,researchers have implemented hardware-aware acceleration strategies,including the use of TensorRT and ONNX-based model compression,to ensure efficient execution on edge devices.These optimizations allow the approach to function effectively in real-time clinical settings,ensuring viability even in environments with limited resources.Future research directions include integrating non-imaging data to facilitate personalized treatment and enhancing computational efficiency for implementation in resource-limited environments.This study highlights the transformative potential of transformer models in multi-modal medical imaging,offering improvements in diagnostic accuracy and patient care outcomes.展开更多
Objective:To investigate the preventive effect of targeted nursing interventions on deep vein thrombosis in patients with hemodialysis catheter indwelling.Methods:A prospective study was conducted involving patients w...Objective:To investigate the preventive effect of targeted nursing interventions on deep vein thrombosis in patients with hemodialysis catheter indwelling.Methods:A prospective study was conducted involving patients who underwent hemodialysis catheter indwelling and were admitted between August 2023 and August 2025,totaling 108 cases.These patients were randomly divided into two groups using a random number table method,with 54 cases in each group.The control group received routine nursing interventions,while the observation group received targeted nursing interventions.The incidence of deep vein thrombosis and hemodynamic indicators were compared between the two groups.Results:The incidence of deep vein thrombosis in the observation group was lower than that in the control group(p<0.05).After two weeks of nursing,the hemodynamic indicators in the observation group were higher than those in the control group(p<0.05).Conclusion:Targeted nursing interventions can effectively prevent deep vein thrombosis and improve hemodynamics in patients with hemodialysis catheter indwelling,making them worthy of clinical promotion.展开更多
文摘BACKGROUND Stress ulcers are common complications in critically ill patients,with a higher incidence observed in older patients following gastrointestinal surgery.This study aimed to develop and evaluate the effectiveness of a multi-modal intervention protocol to prevent stress ulcers in this high-risk population.AIM To assess the impact of a multi-modal intervention on preventing stress ulcers in older intensive care unit(ICU)patients postoperatively.METHODS A randomized controlled trial involving critically ill patients(aged≥65 years)admitted to the ICU after gastrointestinal surgery was conducted.Patients were randomly assigned to either the intervention group,which received a multimodal stress ulcer prevention protocol,or the control group,which received standard care.The primary outcome measure was the incidence of stress ulcers.The secondary outcomes included ulcer healing time,complication rates,and length of hospital stay.RESULTS A total of 200 patients(100 in each group)were included in this study.The intervention group exhibited a significantly lower incidence of stress ulcers than the control group(15%vs 30%,P<0.01).Additionally,the intervention group demonstrated shorter ulcer healing times(mean 5.2 vs 7.8 days,P<0.05),lower complication rates(10%vs 22%,P<0.05),and reduced length of hospital stay(mean 12.3 vs 15.7 days,P<0.05).CONCLUSION This multi-modal intervention protocol significantly reduced the incidence of stress ulcers and improved clinical outcomes in critically ill older patients after gastrointestinal surgery.This comprehensive approach may provide a valuable strategy for managing high-risk populations in intensive care settings.
文摘BACKGROUND Approximately 30%of patients with head and neck cancer experience adverse effects caused by anxiety and depression.Considering the high prevalence,implementing customized interventions to ease adverse emotional states is imperative.AIM To evaluate the efficacy of cognitive behavioral therapy(CBT)-based psychological interventions in improving the psychological well-being and quality of life(QoL)of patients with laryngeal carcinoma.METHODS This study enrolled 120 patients admitted from February 2022 to February 2024.The control group,comprising 50 participants,received standard supportive psychological care,while the research group,consisting 70 participants,underwent CBT-based interventions.Several clinical outcomes were systematically assessed that included postoperative recovery metrics(duration of tracheostomy and nasogastric tube dependence and length of hospitalization),psychological status(Self-Rating Anxiety Scale and Self-Rating Depression Scale),nutritional markers(serum albumin and hemoglobin levels),sleep quality(Self-Rating Scale of Sleep and Athens Insomnia Scale),and QoL(Functional Assessment of Cancer Therapy-Head and Neck).RESULTS The results demonstrated that the research group experienced superior outcomes,with significantly reduced durations of tracheostomy and nasogastric tube dependence,as well as shorter hospital stays,compared with the control group.Additionally,the research group exhibited markedly lower post-intervention Self-Rating Anxiety Scale,Self-Rating Depression Scale,Self-Rating Scale of Sleep,and Athens Insomnia Scale scores,along with minimal but higher change in serum albumin and hemoglobin levels compared with the control group.All five domains of Functional Assessment of Cancer Therapy-Head and Neck showed notable improvements in the research group,exceeding those observed in the control group.CONCLUSION CBT-based psychological support positively affects the mental well-being and QoL of patients with laryngeal carcinoma,highlighting its potential for broader clinical application.
基金Deutsche Forschungsgemeinschaft(DFG,German Research Foundation),project numbers 324633948 and 409784463(DFG grants Hi 678/9-3 and Hi 678/10-2,FOR2953)to HHBundesministerium für Bildung und Forschung-BMBF,project number 16LW0463K to HT.
文摘Microglia are the resident macrophages of the central nervous system.They act as the first line of defense against pathogens and play essential roles in neuroinflammation and tissue repair after brain insult or in neurodegenerative and demyelinating diseases(Borst et al.,2021).Together with infiltrating monocyte-derived macrophages,microglia also play a critical role for brain tumor development,since immunosuppressive interactions between tumor cells and tumor-associated microglia and macrophages(TAM)are linked to malignant progression.This mechanism is of particular relevance in glioblastoma(GB),the deadliest form of brain cancer with a median overall survival of less than 15 months(Khan et al.,2023).Therefore,targeting microglia and macrophage activation is a promising strategy for therapeutic interference in brain disease.
文摘The intersection of visual impairment and mental health has profound effects on quality of life and warrants attention from healthcare providers,educators,and policymakers.With 20 million children under the age of 14 affected globally,older adults also experience significant psychological impact including depression,anxiety,and cognitive impairment.The implications of vision-related challenges extend far beyond mere sight.Depression and anxiety,exacerbated by social isolation and reduced physical activity,underscore the need for comprehensive interventions that address both medical and psychosocial dimensions.By recognizing the profound impact of ocular morbidities like strabismus,myopia,glaucoma,and age-related macular degeneration on mental health and investing in effective treatments and inclusive practices,society can pave the way for a healthier,more equitable future for affected individuals.There is evidence that myopic children experience a higher prevalence of depressive symptoms compared to their normal peers,and interventions like the correction of strabismus can enhance psychological outcome-demonstrating the value of an integrated management approach.
基金Construction Program of the Key Discipline of State Administration of Traditional Chinese Medicine of China(ZYYZDXK-2023069)Research Project of Shanghai Municipal Health Commission (2024QN018)Shanghai University of Traditional Chinese Medicine Science and Technology Development Program (23KFL005)。
文摘Objective To develop a non-invasive predictive model for coronary artery stenosis severity based on adaptive multi-modal integration of traditional Chinese and western medicine data.Methods Clinical indicators,echocardiographic data,traditional Chinese medicine(TCM)tongue manifestations,and facial features were collected from patients who underwent coro-nary computed tomography angiography(CTA)in the Cardiac Care Unit(CCU)of Shanghai Tenth People's Hospital between May 1,2023 and May 1,2024.An adaptive weighted multi-modal data fusion(AWMDF)model based on deep learning was constructed to predict the severity of coronary artery stenosis.The model was evaluated using metrics including accura-cy,precision,recall,F1 score,and the area under the receiver operating characteristic(ROC)curve(AUC).Further performance assessment was conducted through comparisons with six ensemble machine learning methods,data ablation,model component ablation,and various decision-level fusion strategies.Results A total of 158 patients were included in the study.The AWMDF model achieved ex-cellent predictive performance(AUC=0.973,accuracy=0.937,precision=0.937,recall=0.929,and F1 score=0.933).Compared with model ablation,data ablation experiments,and various traditional machine learning models,the AWMDF model demonstrated superior per-formance.Moreover,the adaptive weighting strategy outperformed alternative approaches,including simple weighting,averaging,voting,and fixed-weight schemes.Conclusion The AWMDF model demonstrates potential clinical value in the non-invasive prediction of coronary artery disease and could serve as a tool for clinical decision support.
文摘Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single target”presents significant challenges due to its holistic approach.Network pharmacology and its core theory of network targets connect drugs and diseases from a holistic and systematic perspective based on biological networks,overcoming the limitations of reductionist research models and showing considerable value in TCM research.Recent integration of network target computational and experimental methods with artificial intelligence(AI)and multi-modal multi-omics technologies has substantially enhanced network pharmacology methodology.The advancement in computational and experimental techniques provides complementary support for network target theory in decoding TCM principles.This review,centered on network targets,examines the progress of network target methods combined with AI in predicting disease molecular mechanisms and drug-target relationships,alongside the application of multi-modal multi-omics technologies in analyzing TCM formulae,syndromes,and toxicity.Looking forward,network target theory is expected to incorporate emerging technologies while developing novel approaches aligned with its unique characteristics,potentially leading to significant breakthroughs in TCM research and advancing scientific understanding and innovation in TCM.
文摘Objective:To evaluate the value of rehabilitation nursing based on mind mapping model combined with psychological intervention for patients with nephrotic syndrome(NS).Methods:A total of 60 patients with NS who visited our hospital from January 2024 to December 2024 were selected as samples and randomly divided into groups.The observation group received rehabilitation nursing based on the mind mapping model combined with psychological intervention,while the control group received routine intervention.The differences in emotional scores,self-care ability scores,compliance,and complications were compared between the two groups.Results:The anxiety(SAS)and depression(SDS)scores of the observation group were lower than those of the control group,while the self-care ability scale(ESCA)score was higher than that of the control group(P<0.05).The compliance rate of the observation group was higher than that of the control group(P<0.05).The complication rate of NS in the observation group was lower than that in the control group(P<0.05).Conclusion:Rehabilitation nursing based on the mind mapping model combined with psychological intervention can enhance self-care ability,reduce negative emotions,and reduce complications in NS nursing,which is efficient and feasible.
基金supported by the National Natural Science Foundation of China(Nos.62371323,62401380,U2433217,U2333209,and U20A20161)Natural Science Foundation of Sichuan Province,China(Nos.2025ZNSFSC1476)+2 种基金Sichuan Science and Technology Program,China(Nos.2024YFG0010 and 2024ZDZX0046)the Institutional Research Fund from Sichuan University(Nos.2024SCUQJTX030)the Open Fund of Key Laboratory of Flight Techniques and Flight Safety,CAAC(Nos.GY2024-01A).
文摘With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intelligent SA(ISA).However,the existing AI-based SA approaches often rely on unimodal data and lack a comprehensive description and benchmark of the ISA tasks utilizing multi-modal data for real-time ATC environments.To address this gap,by analyzing the situation awareness procedure of the ATCOs,the ISA task is refined to the processing of the two primary elements,i.e.,spoken instructions and flight trajectories.Subsequently,the ISA is further formulated into Controlling Intent Understanding(CIU)and Flight Trajectory Prediction(FTP)tasks.For the CIU task,an innovative automatic speech recognition and understanding framework is designed to extract the controlling intent from unstructured and continuous ATC communications.For the FTP task,the single-and multi-horizon FTP approaches are investigated to support the high-precision prediction of the situation evolution.A total of 32 unimodal/multi-modal advanced methods with extensive evaluation metrics are introduced to conduct the benchmarks on the real-world multi-modal ATC situation dataset.Experimental results demonstrate the effectiveness of AI-based techniques in enhancing ISA for the ATC environment.
基金supported by the National Social Science Fund of China[18BSH146].
文摘Background:Parenting exerts a profound influence on children’s mental health and behavioral development.Despite the high prevalence of children’s emotional and behavioral problems(CEBP)in China,evidence-based parenting interventions remain scarcely investigated as preventive public health strategies.This pilot study evaluated a school-based intervention for preventing CEBP.Methods:We employed a quasi-experimental design with propensity score matching(PSM)to select 28 families(intervention:n=13;control:n=15)from two matched urban primary schools.Quantitative data from seven validated scales were analyzed using t-tests and ANCOVA.Qualitative insights were derived from 10 semi-structured interviews via thematic analysis.Results:Compared to the control group,the intervention group demonstrated significantly greater improvements in CEBP(p=0.020,Cohen’s d=0.92),parental adjustment(p=0.031,Cohen’s d=0.80),parenting confidence(p=0.003,Cohen’s d=1.04),and parentchild relationships(p=0.001,Cohen’s d=1.46).Non-significant effects were observed for parenting style,parental relationship,and parenting conflict(p>0.05).Qualitative analysis corroborated these findings and further identified contributing factors for non-significant outcomes,including challengeswithmeasurement adaptability and inconsistent co-parenting practices.Conclusions:This pilot study suggests that an authoritative parenting style may be effective and culturally adaptable in China.Positive parenting interventions appear to mitigate CEBP by reducing risk factors and enhancing protective factors.However,improving parental relationships and parenting conflict may require targeted strategies.Given the pilot nature of this PSM-matched study(n=28),the findings should be interpreted as exploratory and used primarily for intervention refinement.
文摘BACKGROUND The development of hepatocellular carcinoma(HCC)is influenced by multiple factors.Interventional therapy offers an effective treatment option for patients with unresectable intermediate-to-advanced HCC.Interventional therapy can induce electrocardiographic(ECG)abnormalities that may be associated with liver dysfunction,electrolyte disorders,and cardiac injury.AIM To explore the ECG alterations and determinants following interventional therapy in patients with HCC.METHODS Sixty patients undergoing interventional treatment for liver cancer were selected as study participants.According to the results of the dynamic ECG examination 1 day after surgery,the patients were divided into an abnormal group(n=21)and a nonabnormal group(n=39).With the help of dynamic ECG examination,the ECG parameters were compared and the baseline data of patients was recorded in the two groups.RESULTS The 24 hours QT interval variability,24 hours normal atrial polarization to ventricular polarization(R-R)interval(standard deviation),24 hours consecutive 5 minutes normal R-R interval,and 24 hours continuous 5 minutes normal R-R interval(standard deviation mean)were lower than patients in the nonabnormal group(P<0.05).The logistic analysis showed that age>60 years,liver function grade B,and postoperative body temperature 38°C were risk factors for abnormal dynamic electrocardiogram in patients with liver cancer intervention(P<0.05).CONCLUSION Interventional therapy for HCC can lead to ECG abnormalities,underscoring the clinical need for enhanced cardiac monitoring to mitigate myocardial complications.
文摘BACKGROUND Simultaneous acute ischemic stroke(AIS)and myocardial infarction(cardio-cerebral ischemic attack)have rarely been reported in the literature.Currently,no clear evidence-based guidelines or clinical trials exist to determine the optimal therapeutic strategy for these patients.CASE SUMMARY We present the case of a 27-year-old Chinese man who simultaneously experie-nced acute concomitant cerebrocardiac infarction(CCI)and painless ST-elevation myocardial infarction.The patient was successfully treated with elective percu-taneous coronary intervention(PCI)after receiving urgent systemic thrombolysis at the standard dose for AIS.CONCLUSION Urgent thrombolysis followed by elective PCI was an appropriate strategy for the management of simultaneous CCI.
基金Shanghai Frontier Science Research Center for Modern Textiles,Donghua University,ChinaOpen Project of Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment,Zhengzhou University of Light Industry,China(No.IM202303)National Key Research and Development Program of China(No.2019YFB1706300)。
文摘A personalized outfit recommendation has emerged as a hot research topic in the fashion domain.However,existing recommendations do not fully exploit user style preferences.Typically,users prefer particular styles such as casual and athletic styles,and consider attributes like color and texture when selecting outfits.To achieve personalized outfit recommendations in line with user style preferences,this paper proposes a personal style guided outfit recommendation with multi-modal fashion compatibility modeling,termed as PSGNet.Firstly,a style classifier is designed to categorize fashion images of various clothing types and attributes into distinct style categories.Secondly,a personal style prediction module extracts user style preferences by analyzing historical data.Then,to address the limitations of single-modal representations and enhance fashion compatibility,both fashion images and text data are leveraged to extract multi-modal features.Finally,PSGNet integrates these components through Bayesian personalized ranking(BPR)to unify the personal style and fashion compatibility,where the former is used as personal style features and guides the output of the personalized outfit recommendation tailored to the target user.Extensive experiments on large-scale datasets demonstrate that the proposed model is efficient on the personalized outfit recommendation.
文摘Liver transplantation,as an effective therapy for patients with liver cancer,plays an important role in improving the quality of life of patients.However,the com-plexity and trauma of liver transplantation can easily lead to the occurrence of malnutrition in patients,and then increase the risk of postoperative complica-tions,which has aroused widespread clinical attention.Reasonable nutritional support can not only maintain the stability of the body’s internal environment,reduce the occurrence of complications,but also promote the recovery of liver and other organ functions.In recent years,with the in-depth understanding of nut-ritional metabolism after liver transplantation,the application of enteral nutrition and parenteral nutrition in nutritional support after liver transplantation has been increasingly extensive and achieved remarkable results.This paper discusses the effect of early postoperative nutritional intervention on patients with liver cancer and liver transplantation,and combined with its mechanism of action,can better understand the effectiveness of intervention,and provide reference for the deve-lopment of scientific and reasonable nutritional support programs in clinical pra-ctice.
文摘This study aims to explore the characteristics of novice teachers’inappropriate behaviors in classroom teaching and their intervention strategies.With the continuous improvement of education quality,novice teachers face increasing challenges in teaching practice.Their inappropriate behaviors not only affect the classroom atmosphere but may also negatively impact students’learning outcomes.Therefore,researching the characteristics of novice teachers’inappropriate behaviors and their intervention strategies holds significant scientific and social value.This study employs a combination of quantitative and qualitative methods to analyze the behavioral patterns of novice teachers in classroom teaching and proposes corresponding intervention strategies.The results indicate that novice teachers’inappropriate behaviors mainly manifest as poor classroom management,monotonous teaching methods,and insufficient interaction with students.Based on these findings,the study proposes a series of effective intervention strategies,including enhancing teacher training,optimizing teaching design,and promoting positive interactions between teachers and students.The conclusions of the study not only provide practical guidance for educational practice but also point out directions for future research,emphasizing the crucial role of teacher professional development in improving teaching quality.
文摘Non-communicable diseases (NCDs) are on the rise worldwide and in developing countries like Botswana. Unhealthy eating habits and lack of proper nutrition knowledge cause non-communicable diseases and affect adolescents. It is in adolescence that eating habits are formed that persist till adulthood. Lifestyle interventions are needed to curb NCDs in adolescents. This paper reports the findings of a study that aimed to validate a lifestyle intervention program and its effect on food intake, physical activity, and nutrition knowledge. It was a clustered randomized control trial study conducted in four (4) junior secondary schools. There were 46 participants, 21 in the control and 25 in the intervention arm, who were blindly assigned to each arm by a statistician. Information and skills on nutrition were imparted using the Information, Motivation, and Behavioral Skills model. The program was implemented for eight (8) weeks hourly after school. A questionnaire was used to collect data pre- and post-intervention. Number, proportion, percentage, and independent t-test (mean and SD or median and IQR, p-value) were calculated using numerical and categorical data. The findings showed that the lifestyle intervention was valid, and there was a slight decrease in the intake of sweets among participants in both trial arms (p = 0.066). There was no significant difference in terms of food intake. Only a small number of participants still ate a few fruits, and there was no change in vegetable intake in both trial arms (p = 0.641). There was no change in the intake of fried foods in both trail arms (p = 0.402). Regarding nutrition knowledge, there was a slight significant difference of p = 0.079 between the trial arms. Though the effect of the lifestyle intervention program was not statistically significant, the results are promising, especially if the duration could be increased to a longer period and a larger sample size included.
基金funded by Research Project,grant number BHQ090003000X03.
文摘Multi-modal Named Entity Recognition(MNER)aims to better identify meaningful textual entities by integrating information from images.Previous work has focused on extracting visual semantics at a fine-grained level,or obtaining entity related external knowledge from knowledge bases or Large Language Models(LLMs).However,these approaches ignore the poor semantic correlation between visual and textual modalities in MNER datasets and do not explore different multi-modal fusion approaches.In this paper,we present MMAVK,a multi-modal named entity recognition model with auxiliary visual knowledge and word-level fusion,which aims to leverage the Multi-modal Large Language Model(MLLM)as an implicit knowledge base.It also extracts vision-based auxiliary knowledge from the image formore accurate and effective recognition.Specifically,we propose vision-based auxiliary knowledge generation,which guides the MLLM to extract external knowledge exclusively derived from images to aid entity recognition by designing target-specific prompts,thus avoiding redundant recognition and cognitive confusion caused by the simultaneous processing of image-text pairs.Furthermore,we employ a word-level multi-modal fusion mechanism to fuse the extracted external knowledge with each word-embedding embedded from the transformerbased encoder.Extensive experimental results demonstrate that MMAVK outperforms or equals the state-of-the-art methods on the two classical MNER datasets,even when the largemodels employed have significantly fewer parameters than other baselines.
基金funded by Research Project,grant number BHQ090003000X03。
文摘Multi-modal knowledge graph completion(MMKGC)aims to complete missing entities or relations in multi-modal knowledge graphs,thereby discovering more previously unknown triples.Due to the continuous growth of data and knowledge and the limitations of data sources,the visual knowledge within the knowledge graphs is generally of low quality,and some entities suffer from the issue of missing visual modality.Nevertheless,previous studies of MMKGC have primarily focused on how to facilitate modality interaction and fusion while neglecting the problems of low modality quality and modality missing.In this case,mainstream MMKGC models only use pre-trained visual encoders to extract features and transfer the semantic information to the joint embeddings through modal fusion,which inevitably suffers from problems such as error propagation and increased uncertainty.To address these problems,we propose a Multi-modal knowledge graph Completion model based on Super-resolution and Detailed Description Generation(MMCSD).Specifically,we leverage a pre-trained residual network to enhance the resolution and improve the quality of the visual modality.Moreover,we design multi-level visual semantic extraction and entity description generation,thereby further extracting entity semantics from structural triples and visual images.Meanwhile,we train a variational multi-modal auto-encoder and utilize a pre-trained multi-modal language model to complement the missing visual features.We conducted experiments on FB15K-237 and DB13K,and the results showed that MMCSD can effectively perform MMKGC and achieve state-of-the-art performance.
文摘BACKGROUND Excessive noise in healthcare environments—commonly described as"unwanted sound"—has been linked to a range of negative impacts on both patients and staff.In clinical settings,elevated noise levels have been associated with sleep disruption,heightened cardiovascular stress,and an increased risk of delirium in patients.Among healthcare workers,noise can impair focus and cognitive performance,potentially compromising care quality.AIM To evaluate the effectiveness of educational and behavioural interventions in reducing noise levels within intensive care units(ICUs),recognizing their potential impact on patient outcomes and healthcare effectiveness.METHODS A prospective interventional study in two Singaporean teaching hospitals compared peak and average sound levels between control and intervention groups.An educational and behavioural intervention comprising talks,posters,and self-audits by nurse champions was initiated in two ICUs in one hospital on November 18,2023.Sound measurements were collected at 4 Locations within each ICU before and after intervention.Baseline measurements were taken from October 22,2023 to October 29,2023,and post-intervention measurements from December 21,2023 to December 22,2023.The hospitals served as the primary exposure variable,controlled for ICU type(medical vs surgical)and hour of the day.RESULTS Our analysis generated 48 pairs of peak and average sound level readings for each unit(control n=48 readings;intervention n=48 readings).The effect of the intervention was associated with a significant 4.8 dB decrease in average sound level(P=0.009)and a nonsignificant 4.3 dB decrease in peak sound level(P=0.104),adjusted for hour of day and type of ICU.CONCLUSION Educational and behavioural interventions successfully reduced average sound levels,emphasizing their positive impact on noise control.These findings contribute valuable insights for optimizing noise reduction efforts in critical care settings.Future studies may explore additional systemic and environmental interventions to enhance noise management strategies.
基金supported by the Deanship of Research and Graduate Studies at King Khalid University under Small Research Project grant number RGP1/139/45.
文摘Integrating multiple medical imaging techniques,including Magnetic Resonance Imaging(MRI),Computed Tomography,Positron Emission Tomography(PET),and ultrasound,provides a comprehensive view of the patient health status.Each of these methods contributes unique diagnostic insights,enhancing the overall assessment of patient condition.Nevertheless,the amalgamation of data from multiple modalities presents difficulties due to disparities in resolution,data collection methods,and noise levels.While traditional models like Convolutional Neural Networks(CNNs)excel in single-modality tasks,they struggle to handle multi-modal complexities,lacking the capacity to model global relationships.This research presents a novel approach for examining multi-modal medical imagery using a transformer-based system.The framework employs self-attention and cross-attention mechanisms to synchronize and integrate features across various modalities.Additionally,it shows resilience to variations in noise and image quality,making it adaptable for real-time clinical use.To address the computational hurdles linked to transformer models,particularly in real-time clinical applications in resource-constrained environments,several optimization techniques have been integrated to boost scalability and efficiency.Initially,a streamlined transformer architecture was adopted to minimize the computational load while maintaining model effectiveness.Methods such as model pruning,quantization,and knowledge distillation have been applied to reduce the parameter count and enhance the inference speed.Furthermore,efficient attention mechanisms such as linear or sparse attention were employed to alleviate the substantial memory and processing requirements of traditional self-attention operations.For further deployment optimization,researchers have implemented hardware-aware acceleration strategies,including the use of TensorRT and ONNX-based model compression,to ensure efficient execution on edge devices.These optimizations allow the approach to function effectively in real-time clinical settings,ensuring viability even in environments with limited resources.Future research directions include integrating non-imaging data to facilitate personalized treatment and enhancing computational efficiency for implementation in resource-limited environments.This study highlights the transformative potential of transformer models in multi-modal medical imaging,offering improvements in diagnostic accuracy and patient care outcomes.
文摘Objective:To investigate the preventive effect of targeted nursing interventions on deep vein thrombosis in patients with hemodialysis catheter indwelling.Methods:A prospective study was conducted involving patients who underwent hemodialysis catheter indwelling and were admitted between August 2023 and August 2025,totaling 108 cases.These patients were randomly divided into two groups using a random number table method,with 54 cases in each group.The control group received routine nursing interventions,while the observation group received targeted nursing interventions.The incidence of deep vein thrombosis and hemodynamic indicators were compared between the two groups.Results:The incidence of deep vein thrombosis in the observation group was lower than that in the control group(p<0.05).After two weeks of nursing,the hemodynamic indicators in the observation group were higher than those in the control group(p<0.05).Conclusion:Targeted nursing interventions can effectively prevent deep vein thrombosis and improve hemodynamics in patients with hemodialysis catheter indwelling,making them worthy of clinical promotion.
