BACKGROUND Preoperative anxiety is a significant concern for patients,as it affects surgical outcomes,satisfaction,and pain perception.Although both anxiety and pain are common in surgical settings,their relationship ...BACKGROUND Preoperative anxiety is a significant concern for patients,as it affects surgical outcomes,satisfaction,and pain perception.Although both anxiety and pain are common in surgical settings,their relationship with personality traits has not been previously investigated in the Lebanese population.AIM To examine the prevalence of preoperative anxiety,pain perception,and personality traits among Lebanese surgical patients,and to assess the associations between these factors.METHODS A descriptive cross-sectional study was conducted between April 2024 and January 2025 across Lebanese hospitals.A total of 392 adult patients were recruited through convenience sampling.Data were collected using a questionnaire that included sociodemographic,clinical,and surgical variables,the Amsterdam Preoperative Anxiety and Information Scale for anxiety,the Visual Analog Scale and Numerical Pain Rating Scale for preoperative pain,and the Ten-Item Personality Inventory for personality traits.Ethical approval was obtained from the Institutional Review Boards of Makassed General Hospital and Hammoud University Medical Center.RESULTS Overall,25%of participants experienced preoperative anxiety,and 34.5%reported moderate pain.Personality assessment showed that the majority of participants had moderate extraversion(84.1%),moderate emotional stability(65.1%),high conscientiousness(61%),high agreeableness(54.1%),and moderate openness(49.2%).High conscientiousness was significantly associated with higher pain perception(P<0.05),while high emotional stability was associated with lower levels of anxiety(P<0.05).No significant association was found between preoperative anxiety and pain(P>0.05).CONCLUSION This study challenges the assumption that preoperative anxiety and pain are directly correlated and highlights the role of personality traits in shaping patient experience.These findings support the potential value of integrating psychological profiling into preoperative care and lay the groundwork for developing personalized interventions to improve patient-centered surgical outcomes.展开更多
Therapy discontinuation in inflammatory bowel disease,particularly involving immunomodulators,biologics,and small molecules,remains a controversial and evolving topic.This letter reflects on developments following the...Therapy discontinuation in inflammatory bowel disease,particularly involving immunomodulators,biologics,and small molecules,remains a controversial and evolving topic.This letter reflects on developments following the publication by Meštrovićet al,emphasizing the complex balance between risks of relapse,antidrug antibody formation,and potential complications of long-term immunosuppression.Recent evidence underscores high relapse rates following withdrawal-especially of anti-tumor necrosis factor agents-and highlights the lack of robust data for newer biologics.Updated guidelines from European Crohn’s and Colitis Organization,British Society of Gastroenterology,and American College of Gastroenterology all support cautious and individualized approaches,with strict criteria and close follow-up,particularly in Crohn’s disease.For ulcerative colitis,therapeutic cycling remains insufficiently addressed.We proposed a flowchart to support clinical decision-making and stress the importance of shared decisionmaking in the era of personalized medicine since,despite new drug classes and evolving strategies,the therapeutic ceiling in inflammatory bowel disease has yet to be fully overcome.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
This case study describes the care provided to a female patient with borderline personality disorder (BPD) who presented to the emergency department (ED). While people with borderline personality disorder use emergenc...This case study describes the care provided to a female patient with borderline personality disorder (BPD) who presented to the emergency department (ED). While people with borderline personality disorder use emergency services frequently, clinicians often face difficulties when providing medical and behavioral services to these patients. It may be difficult for nurse practitioners to determine if a patient with BPD who presents to the ED in crisis should be admitted, medicated, observed, or discharged. Self-harm is frequently confused with suicide attempts, which can result in unnecessary hospitalizations. This case study seeks to examine the proper management and difficulties encountered by healthcare providers in managing crises involving individuals with BPD in ED settings. The case study underscores the significance of thorough evaluation, recognition of BPD characteristics, active engagement in treatment, the therapeutic alliance, and the emphasis on interpersonal connections and stressors alongside the utilization of psychopharmacology.展开更多
Objectives:To explore the efficacy and safety of virtual reality(VR)in relieving negative emotions in patients with breast cancer with different personalities.Methods:A randomized controlled trial was conducted.Betwee...Objectives:To explore the efficacy and safety of virtual reality(VR)in relieving negative emotions in patients with breast cancer with different personalities.Methods:A randomized controlled trial was conducted.Between April 2023 and October 2023,we enrolled patients with breast cancer treated in the Department of Breast Cancer and Oncology at Sun Yat-Sen Memorial Hospital,Sun Yat-Sen University,Guangdong Province.The patients were randomly divided into an intervention group(n=118)and a control group(n=119)using block randomization.The intervention group received the VR intervention 3-5 times over 5±2 weeks using natural landscapes with music or relaxation guidance,and the duration of each VR intervention was 15±3 min.The control group received routine nursing care,including disease education and psychological counseling.Patients were assessed using the Type D Scale,Positive and Negative Affect Scale,and Distress Thermometer,and adverse events during the intervention were recorded.Results:Overall,85 patients completed the study(44 in the intervention group and 41 in the control group).Patients with Type D personalities showed more negative emotions[25.0(21.5,27.5)vs.19.0(16.0,24.0),P=0.001]and distressed attitudes[4.0(2.0,5.0)vs.3.0(1.0,4.0),P=0.020]with fewer positive emotions(27.2±5.6 vs.31.0±5.9,P=0.014)than those with non-Type D personalities.Total population analysis revealed no significant differences between the groups.However,in the subgroup analysis,patients with Type D personalities in the intervention group showed greater relief from negative emotions than those in the control group[median difference,-5.0(-9.0,-2.5)vs.-2.0(-4.0,2.0),P=0.046].No significant differences were found between groups of patients with non-Type D personality traits.The proportion of adverse events was not significantly different between groups(P=0.110).Conclusions:Breast cancer patients with Type D personalities suffer more severe negative emotions and distress,and more attention should be paid to them.VR intervention significantly and safely reduced negative emotions in patients with Type D personalities.展开更多
Federated learning is a machine learning framework designed to protect privacy by keeping training data on clients’devices without sharing private data.It trains a global model through collaboration between clients a...Federated learning is a machine learning framework designed to protect privacy by keeping training data on clients’devices without sharing private data.It trains a global model through collaboration between clients and the server.However,the presence of data heterogeneity can lead to inefficient model training and even reduce the final model’s accuracy and generalization capability.Meanwhile,data scarcity can result in suboptimal cluster distributions for few-shot clients in centralized clustering tasks,and standalone personalization tasks may cause severe overfitting issues.To address these limitations,we introduce a federated learning dual optimization model based on clustering and personalization strategy(FedCPS).FedCPS adopts a decentralized approach,where clients identify their cluster membership locally without relying on a centralized clustering algorithm.Building on this,FedCPS introduces personalized training tasks locally,adding a regularization term to control deviations between local and cluster models.This improves the generalization ability of the final model while mitigating overfitting.The use of weight-sharing techniques also reduces the computational cost of central machines.Experimental results on MNIST,FMNIST,CIFAR10,and CIFAR100 datasets demonstrate that our method achieves better personalization effects compared to other personalized federated learning methods,with an average test accuracy improvement of 0.81%–2.96%.Meanwhile,we adjusted the proportion of few-shot clients to evaluate the impact on accuracy across different methods.The experiments show that FedCPS reduces accuracy by only 0.2%–3.7%,compared to 2.1%–10%for existing methods.Our method demonstrates its advantages across diverse data environments.展开更多
With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths ha...With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths have become an important direction of intelligent teaching reform.The traditional“one-size-fits-all”teaching model has gradually failed to meet the individualized learning needs of students.However,through the advantages of data analysis and real-time feedback,AI technology can provide tailor-made teaching content and learning paths based on students’learning progress,interests,and abilities.This study explores the innovation of the personalized learning path model based on AI technology,and analyzes the potential and challenges of this model in improving teaching effectiveness,promoting the all-round development of students,and optimizing the interaction between teachers and students.Through case analysis and empirical research,this paper summarizes the implementation methods of the AI-driven personalized learning path,the innovation of teaching models,and their application prospects in educational reform.Meanwhile,the research also discussed the ethical issues of AI technology in education,data privacy protection,and its impact on the teacher-student relationship,and proposed corresponding solutions.展开更多
Hepatocellular carcinoma(HCC)recurrence after liver transplantation(LT)presents a significant challenge,with recurrence rates ranging from 8%to 20%globally.Current biomarkers,such as alpha-fetoprotein(AFP)and des-gamm...Hepatocellular carcinoma(HCC)recurrence after liver transplantation(LT)presents a significant challenge,with recurrence rates ranging from 8%to 20%globally.Current biomarkers,such as alpha-fetoprotein(AFP)and des-gamma-carboxy prothrombin(DCP),lack specificity,limiting their utility in risk strati-fication.YKL-40,a glycoprotein involved in extracellular matrix remodeling,hepatic stellate cell activation,and immune modulation,has emerged as a promising biomarker for post-LT surveillance.Elevated serum levels of YKL-40 are associated with advanced liver disease,tumor progression,and poorer post-LT outcomes,highlighting its potential to address gaps in early detection and personalized management of HCC recurrence.This manuscript synthesizes clinical and mechanistic evidence to evaluate YKL-40’s predictive utility in post-LT care.While preliminary findings demonstrate its specificity for liver-related pathologies,challenges remain,including assay standardization,lack of pro-spective validation,and the need to distinguish between malignant and non-malignant causes of elevated levels.Integrating YKL-40 into multi-biomarker panels with AFP and DCP could enhance predictive accuracy and enable tailored therapeutic strategies.Future research should focus on multicenter studies to validate YKL-40’s clinical utility,address confounding factors like graft rejection and systemic inflammation,and explore its role in predictive models driven by emerging technologies such as artificial intelligence.YKL-40 holds transformative potential in reshaping post-LT care through precision medicine,providing a pathway for better outcomes and improved management of high-risk LT recipients.展开更多
Cardiovascular diseases are the leading cause of death,requiring innovative approaches for prevention,diagnosis,and treatment.Personalized medicine customizes interventions according to individual characteristics,with...Cardiovascular diseases are the leading cause of death,requiring innovative approaches for prevention,diagnosis,and treatment.Personalized medicine customizes interventions according to individual characteristics,with artificial intelligence(AI)playing a key role in analyzing complex data to improve diagnostic accuracy,predict outcomes,and optimize therapies.AI can identify patterns in imaging and biomarkers,facilitating the earlier detection of medical conditions.Wearable devices and health applications facilitate continuous monitoring and personalized care.Emerging fields such as digital Chinese medicine offer additional perspectives by integrating traditional diagnostic principles with modern digital tools,contributing to holistic and individualized cardiovascular care.This study examines the advancements and challenges in personalized cardiovascular medicine,highlighting the need to address issues such as data privacy,algorithmic bias,and accessibility to promote the equitable application of personalized medicine.展开更多
Network architectures assisted by Generative Artificial Intelligence(GAI)are envisioned as foundational elements of sixth-generation(6G)communication system.To deliver ubiquitous intelligent services and meet diverse ...Network architectures assisted by Generative Artificial Intelligence(GAI)are envisioned as foundational elements of sixth-generation(6G)communication system.To deliver ubiquitous intelligent services and meet diverse service requirements,6G network architecture should offer personalized services to various mobile devices.Federated learning(FL)with personalized local training,as a privacypreserving machine learning(ML)approach,can be applied to address these challenges.In this paper,we propose a meta-learning-based personalized FL(PFL)method that improves both communication and computation efficiency by utilizing over-the-air computations.Its“pretraining-and-fine-tuning”principle makes it particularly suitable for enabling edge nodes to access personalized GAI services while preserving local privacy.Experiment results demonstrate the outperformance and efficacy of the proposed algorithm,and notably indicate enhanced communication efficiency without compromising accuracy.展开更多
Objective: To explore the effect of Health Action Process Approach (HAPA) theory in patients with type D personality psoriasis. Methods: A total of 66 patients with type D personality psoriasis admitted to the dermato...Objective: To explore the effect of Health Action Process Approach (HAPA) theory in patients with type D personality psoriasis. Methods: A total of 66 patients with type D personality psoriasis admitted to the dermatology department of a top-three hospital in Jingzhou City from November 2022 to July 2023 were selected and divided into control group and test group with 33 cases in each group by random number table method. The control group received routine health education, and the experimental group received health education based on the HAPA theory. Chronic disease self-efficacy scale, hospital anxiety and depression scale and skin disease quality of life scale were used to evaluate the effect of intervention. Results: After 3 months of intervention, the scores of self-efficacy in experimental group were higher than those in control group (P P Conclusion: Health education based on the theory of HAPA can enhance the self-efficacy of patients with type D personality psoriasis, relieve negative emotions and improve their quality of life.展开更多
Objective:The combination of science and art in nursing is essential for providing effective care.Since art is inherent and a part of human personality traits,it is believed that nurses’personality traits are importa...Objective:The combination of science and art in nursing is essential for providing effective care.Since art is inherent and a part of human personality traits,it is believed that nurses’personality traits are important to achieve this cohesive combination in nursing.Accordingly,this study was conducted to determine the relationship between nurses’personality traits and the esthetics of nursing care.Methods:A cross-sectional descriptive design was employed.Study participants that consisted of 95 nurses and 285 patients from health centers in Iran were selected by convenience sampling method.Measures included the five-factor personality questionnaires(NEO-FFI)scale and Esthetics of Nursing Care Scale(ENCS).Results:The findings indicated a significant relationship between neuroticism(r=−0.149,P=0.028)and extraversion traits(r=0.136,P=0.045)of nurses in esthetics nursing care.In this study,no significant relationship was found between the personality traits and esthetics of nursing care using nurses’demographic information.Conclusions:The esthetics of nursing care depends on nurse personality traits.Since the art of nursing complements the expected care,it is suggested that nursing managers pay attention to the personality traits of nurses in planning to provide effective care.展开更多
The requirement for precise detection and recognition of target pedestrians in unprocessed real-world imagery drives the formulation of person search as an integrated technological framework that unifies pedestrian de...The requirement for precise detection and recognition of target pedestrians in unprocessed real-world imagery drives the formulation of person search as an integrated technological framework that unifies pedestrian detection and person re-identification(Re-ID).However,the inherent discrepancy between the optimization objectives of coarse-grained localization in pedestrian detection and fine-grained discriminative learning in Re-ID,combined with the substantial performance degradation of Re-ID during joint training caused by the Faster R-CNN-based branch,collectively constitutes a critical bottleneck for person search.In this work,we propose a cascaded person searchmodel(SeqXt)based on SeqNet and ConvNeXt that adopts a sequential end-to-end network as its core architecture,artfully integrates the design logic of the two-stepmethod and one-step method framework,and concurrently incorporates the two-step method’s advantage in efficient subtask handling while preserving the one-step method’s efficiency in end-toend training.Firstly,we utilize ConvNeXt-Base as the feature extraction module,which incorporates part of the design concept of Transformer,enhances the consideration of global context information,and boosts feature discrimination through an implicit self-attention mechanism.Secondly,we introduce prototype-guided normalization for calibrating the feature distribution,which leverages the archetype features of individual identities to calibrate the feature distribution and thereby prevents features from being overly inclined towards frequently occurring IDs,notably improving the intra-class compactness and inter-class separability of person identities.Finally,we put forward an innovative loss function named the Dynamic Online Instance Matching Loss Function(DOIM),which employs the hard sample assistantmethod to adaptively update the lookup table(LUT)and the circular queue(CQ)and aims to further enhance the distinctiveness of features between classes.Experimental results on the public datasets CUHK-SYSU and PRWand the private dataset UESTC-PS show that the proposed method achieves state-of-the-art results.展开更多
This study investigated the political,economic,social,and cultural environment perceptions on international students that define their acculturation and health related quality of life.Participants were 117 internation...This study investigated the political,economic,social,and cultural environment perceptions on international students that define their acculturation and health related quality of life.Participants were 117 international students from 32 countries attending a Chinese university(females=43%,mean age=21.17 years,SD=4.45 years).They reported on their acculturation to China and physical and psychological well-being.Results from t-tests and correlation analyses indicate political liberals had more positive attitudes toward China than the conservatives,and higher self-reported physical and psychological results.Higher scores on the“interdependence”dimension of self-construal,as well as the“extraversion”and“emotional stability”dimensions of personality traits,were associated with more positive views of China and better health outcomes.These findings are consistent with Berry’s framework for acculturation,which posits that individual-level variables are related to cultural adaptation,and that cultural adaptation is associated with improved physical and mental health.International student offices at host universities should implement comprehensive support programs,including language assistance,cultural orientation,and social integration initiatives to effectively enhance the health related quality of life of international students.展开更多
Personalized nursing is a necessary means to improve the satisfaction of emergency pediatric nursing.It can enhance the responsiveness of nursing services,strengthen the emotional connection between nurses and patient...Personalized nursing is a necessary means to improve the satisfaction of emergency pediatric nursing.It can enhance the responsiveness of nursing services,strengthen the emotional connection between nurses and patients,and provide a theoretical basis for clinical practice.Therefore,in the context of the new era,it is necessary to deeply analyze the essence and connotation of personalized nursing,and analyze the existing deficiencies in current emergency pediatric personalized nursing,so as to develop effective improvement plans.Research shows that personalized nursing can significantly improve the satisfaction of emergency pediatric nursing,largely avoid nursing risks,and has strong clinical application value.This article summarizes and explores the research on the influence of personalized nursing on improving the satisfaction of emergency pediatric nursing,and puts forward corresponding views.展开更多
Social media outlets deliver customers a medium for communication,exchange,and expression of their thoughts with others.The advent of social networks and the fast escalation of the quantity of data have created opport...Social media outlets deliver customers a medium for communication,exchange,and expression of their thoughts with others.The advent of social networks and the fast escalation of the quantity of data have created opportunities for textual evaluation.Utilising the user corpus,characteristics of social platform users,and other data,academic research may accurately discern the personality traits of users.This research examines the traits of consumer personalities.Usually,personality tests administered by psychological experts via interviews or self-report questionnaires are costly,time-consuming,complex,and labour-intensive.Currently,academics in computational linguistics are increasingly focused on predicting personality traits from social media data.An individual’s personality comprises their traits and behavioral habits.To address this distinction,we propose a novel LSTMapproach(BERT-LIWC-LSTM)that simultaneously incorporates users’enduring and immediate personality characteristics for textual personality recognition.Long-termPersonality Encoding in the proposed paradigmcaptures and represents persisting personality traits.Short-termPersonality Capturing records changing personality states.Experimental results demonstrate that the designed BERT-LIWC-LSTM model achieves an average improvement in accuracy of 3.41% on the Big Five dataset compared to current methods,thereby justifying the efficacy of encoding both stable and dynamic personality traits simultaneously through long-and short-term feature interaction.展开更多
Changing a person’s posture and low resolution are the key challenges for person re-identification(ReID)in various deep learning applications.In this paper,we introduce an innovative architecture using a dual attenti...Changing a person’s posture and low resolution are the key challenges for person re-identification(ReID)in various deep learning applications.In this paper,we introduce an innovative architecture using a dual attention network that includes an attentionmodule and a joint measurement module of spatial-temporal information.The proposed approach can be classified into two main tasks.Firstly,the spatial attention feature map is formed by aggregating features in the spatial dimension.Additionally,the same operation is carried out on the channel dimension to formchannel attention featuremaps.Therefore,the receptive field size is adjusted adaptively tomitigate the changing person posture issue.Secondly,we use a joint measurement method for the spatial-temporal information to fully harness the data,and it can also naturally integrate the information into the visual features of supervised ReID and hence overcome the low resolution problem.The experimental results indicate that our proposed algorithm markedly improves the accuracy in addressing changing human postures and low-resolution issues compared with contemporary leading techniques.The proposed method shows superior outcomes on widely recognized benchmarks,which are the Market-1501,MSMT17,and DukeMTMC-reID datasets.Furthermore,the proposed algorithmattains a Rank-1 accuracy of 97.4% and 94.9% mAP(mean Average Precision)on the Market-1501 dataset.Moreover,it achieves a 94.2% Rank-1 accuracy and 91.8% mAP on the DukeMTMC-reID dataset.展开更多
Diabetes mellitus(DM)comprises distinct subtypes-including type 1 DM,type 2 DM,and gestational DM-all characterized by chronic hyperglycemia and sub-stantial morbidity.Conventional diagnostic and therapeutic strategie...Diabetes mellitus(DM)comprises distinct subtypes-including type 1 DM,type 2 DM,and gestational DM-all characterized by chronic hyperglycemia and sub-stantial morbidity.Conventional diagnostic and therapeutic strategies often fall short in addressing the complex,multifactorial nature of DM.This review ex-plores how multi-omics integration enhances our mechanistic understanding of DM and informs emerging personalized therapeutic approaches.We consolidated genomic,transcriptomic,proteomic,metabolomic,and microbiomic data from major databases and peer-reviewed publications(2015-2025),with an emphasis on clinical relevance.Multi-omics investigations have identified convergent mole-cular networks underlyingβ-cell dysfunction,insulin resistance,and diabetic complications.The combination of metabolomics and microbiomics highlights critical interactions between metabolic intermediates and gut dysbiosis.Novel biomarkers facilitate early detection of DM and its complications,while single-cell multi-omics and machine learning further refine risk stratification.By dissecting DM heterogeneity more precisely,multi-omics integration enables targeted in-terventions and preventive strategies.Future efforts should focus on data har-monization,ethical considerations,and real-world validation to fully leverage multi-omics in addressing the global DM burden.展开更多
Objective:To investigate the distribution of health literacy(HL)levels and the association of HL with proactive personality in patients with permanent colostomy.Methods:A cross-sectional study was conducted to measure...Objective:To investigate the distribution of health literacy(HL)levels and the association of HL with proactive personality in patients with permanent colostomy.Methods:A cross-sectional study was conducted to measure proactive personality and HL using validated scales.A total of 172 patients with permanent colostomy were selected from January 2021 to May 2022 in Yantai City,China.Descriptive statistics,t-test,ANOVA,Pearson correlation analysis,and multiple linear regression analysis techniques were used.Results:The results obtained from the study showed that the HL status of the participants was moderate.The correlation between participants’total HL scores and proactive personality scores was 0.417(P-value<0.001).In addition,HL showed statistically significant differences according to education level,place of residence,profession,and average monthly household income.Conclusions:This study showed that patients with higher proactive personality scores had higher HL.The key stakeholders require several positive strategies to improve the HL of patients with permanent colostomy by cultivating their proactive personalities,and these important policies will help to improve patient health and quality of life.展开更多
文摘BACKGROUND Preoperative anxiety is a significant concern for patients,as it affects surgical outcomes,satisfaction,and pain perception.Although both anxiety and pain are common in surgical settings,their relationship with personality traits has not been previously investigated in the Lebanese population.AIM To examine the prevalence of preoperative anxiety,pain perception,and personality traits among Lebanese surgical patients,and to assess the associations between these factors.METHODS A descriptive cross-sectional study was conducted between April 2024 and January 2025 across Lebanese hospitals.A total of 392 adult patients were recruited through convenience sampling.Data were collected using a questionnaire that included sociodemographic,clinical,and surgical variables,the Amsterdam Preoperative Anxiety and Information Scale for anxiety,the Visual Analog Scale and Numerical Pain Rating Scale for preoperative pain,and the Ten-Item Personality Inventory for personality traits.Ethical approval was obtained from the Institutional Review Boards of Makassed General Hospital and Hammoud University Medical Center.RESULTS Overall,25%of participants experienced preoperative anxiety,and 34.5%reported moderate pain.Personality assessment showed that the majority of participants had moderate extraversion(84.1%),moderate emotional stability(65.1%),high conscientiousness(61%),high agreeableness(54.1%),and moderate openness(49.2%).High conscientiousness was significantly associated with higher pain perception(P<0.05),while high emotional stability was associated with lower levels of anxiety(P<0.05).No significant association was found between preoperative anxiety and pain(P>0.05).CONCLUSION This study challenges the assumption that preoperative anxiety and pain are directly correlated and highlights the role of personality traits in shaping patient experience.These findings support the potential value of integrating psychological profiling into preoperative care and lay the groundwork for developing personalized interventions to improve patient-centered surgical outcomes.
文摘Therapy discontinuation in inflammatory bowel disease,particularly involving immunomodulators,biologics,and small molecules,remains a controversial and evolving topic.This letter reflects on developments following the publication by Meštrovićet al,emphasizing the complex balance between risks of relapse,antidrug antibody formation,and potential complications of long-term immunosuppression.Recent evidence underscores high relapse rates following withdrawal-especially of anti-tumor necrosis factor agents-and highlights the lack of robust data for newer biologics.Updated guidelines from European Crohn’s and Colitis Organization,British Society of Gastroenterology,and American College of Gastroenterology all support cautious and individualized approaches,with strict criteria and close follow-up,particularly in Crohn’s disease.For ulcerative colitis,therapeutic cycling remains insufficiently addressed.We proposed a flowchart to support clinical decision-making and stress the importance of shared decisionmaking in the era of personalized medicine since,despite new drug classes and evolving strategies,the therapeutic ceiling in inflammatory bowel disease has yet to be fully overcome.
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This case study describes the care provided to a female patient with borderline personality disorder (BPD) who presented to the emergency department (ED). While people with borderline personality disorder use emergency services frequently, clinicians often face difficulties when providing medical and behavioral services to these patients. It may be difficult for nurse practitioners to determine if a patient with BPD who presents to the ED in crisis should be admitted, medicated, observed, or discharged. Self-harm is frequently confused with suicide attempts, which can result in unnecessary hospitalizations. This case study seeks to examine the proper management and difficulties encountered by healthcare providers in managing crises involving individuals with BPD in ED settings. The case study underscores the significance of thorough evaluation, recognition of BPD characteristics, active engagement in treatment, the therapeutic alliance, and the emphasis on interpersonal connections and stressors alongside the utilization of psychopharmacology.
基金supported by a project of the National Natural Science Foundation of China:Research on the integration of artificial intelligence and virtual reality technology to promote psychological rehabilitation of breast cancer patients with different personalities(project approval no.82073408).
文摘Objectives:To explore the efficacy and safety of virtual reality(VR)in relieving negative emotions in patients with breast cancer with different personalities.Methods:A randomized controlled trial was conducted.Between April 2023 and October 2023,we enrolled patients with breast cancer treated in the Department of Breast Cancer and Oncology at Sun Yat-Sen Memorial Hospital,Sun Yat-Sen University,Guangdong Province.The patients were randomly divided into an intervention group(n=118)and a control group(n=119)using block randomization.The intervention group received the VR intervention 3-5 times over 5±2 weeks using natural landscapes with music or relaxation guidance,and the duration of each VR intervention was 15±3 min.The control group received routine nursing care,including disease education and psychological counseling.Patients were assessed using the Type D Scale,Positive and Negative Affect Scale,and Distress Thermometer,and adverse events during the intervention were recorded.Results:Overall,85 patients completed the study(44 in the intervention group and 41 in the control group).Patients with Type D personalities showed more negative emotions[25.0(21.5,27.5)vs.19.0(16.0,24.0),P=0.001]and distressed attitudes[4.0(2.0,5.0)vs.3.0(1.0,4.0),P=0.020]with fewer positive emotions(27.2±5.6 vs.31.0±5.9,P=0.014)than those with non-Type D personalities.Total population analysis revealed no significant differences between the groups.However,in the subgroup analysis,patients with Type D personalities in the intervention group showed greater relief from negative emotions than those in the control group[median difference,-5.0(-9.0,-2.5)vs.-2.0(-4.0,2.0),P=0.046].No significant differences were found between groups of patients with non-Type D personality traits.The proportion of adverse events was not significantly different between groups(P=0.110).Conclusions:Breast cancer patients with Type D personalities suffer more severe negative emotions and distress,and more attention should be paid to them.VR intervention significantly and safely reduced negative emotions in patients with Type D personalities.
基金supported by the Foundation of President of Hebei University(XZJJ202303).
文摘Federated learning is a machine learning framework designed to protect privacy by keeping training data on clients’devices without sharing private data.It trains a global model through collaboration between clients and the server.However,the presence of data heterogeneity can lead to inefficient model training and even reduce the final model’s accuracy and generalization capability.Meanwhile,data scarcity can result in suboptimal cluster distributions for few-shot clients in centralized clustering tasks,and standalone personalization tasks may cause severe overfitting issues.To address these limitations,we introduce a federated learning dual optimization model based on clustering and personalization strategy(FedCPS).FedCPS adopts a decentralized approach,where clients identify their cluster membership locally without relying on a centralized clustering algorithm.Building on this,FedCPS introduces personalized training tasks locally,adding a regularization term to control deviations between local and cluster models.This improves the generalization ability of the final model while mitigating overfitting.The use of weight-sharing techniques also reduces the computational cost of central machines.Experimental results on MNIST,FMNIST,CIFAR10,and CIFAR100 datasets demonstrate that our method achieves better personalization effects compared to other personalized federated learning methods,with an average test accuracy improvement of 0.81%–2.96%.Meanwhile,we adjusted the proportion of few-shot clients to evaluate the impact on accuracy across different methods.The experiments show that FedCPS reduces accuracy by only 0.2%–3.7%,compared to 2.1%–10%for existing methods.Our method demonstrates its advantages across diverse data environments.
基金The 2024 Guangdong University of Science and Technology Teaching,Science and Innovation Project(GKJXXZ2024028)。
文摘With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths have become an important direction of intelligent teaching reform.The traditional“one-size-fits-all”teaching model has gradually failed to meet the individualized learning needs of students.However,through the advantages of data analysis and real-time feedback,AI technology can provide tailor-made teaching content and learning paths based on students’learning progress,interests,and abilities.This study explores the innovation of the personalized learning path model based on AI technology,and analyzes the potential and challenges of this model in improving teaching effectiveness,promoting the all-round development of students,and optimizing the interaction between teachers and students.Through case analysis and empirical research,this paper summarizes the implementation methods of the AI-driven personalized learning path,the innovation of teaching models,and their application prospects in educational reform.Meanwhile,the research also discussed the ethical issues of AI technology in education,data privacy protection,and its impact on the teacher-student relationship,and proposed corresponding solutions.
文摘Hepatocellular carcinoma(HCC)recurrence after liver transplantation(LT)presents a significant challenge,with recurrence rates ranging from 8%to 20%globally.Current biomarkers,such as alpha-fetoprotein(AFP)and des-gamma-carboxy prothrombin(DCP),lack specificity,limiting their utility in risk strati-fication.YKL-40,a glycoprotein involved in extracellular matrix remodeling,hepatic stellate cell activation,and immune modulation,has emerged as a promising biomarker for post-LT surveillance.Elevated serum levels of YKL-40 are associated with advanced liver disease,tumor progression,and poorer post-LT outcomes,highlighting its potential to address gaps in early detection and personalized management of HCC recurrence.This manuscript synthesizes clinical and mechanistic evidence to evaluate YKL-40’s predictive utility in post-LT care.While preliminary findings demonstrate its specificity for liver-related pathologies,challenges remain,including assay standardization,lack of pro-spective validation,and the need to distinguish between malignant and non-malignant causes of elevated levels.Integrating YKL-40 into multi-biomarker panels with AFP and DCP could enhance predictive accuracy and enable tailored therapeutic strategies.Future research should focus on multicenter studies to validate YKL-40’s clinical utility,address confounding factors like graft rejection and systemic inflammation,and explore its role in predictive models driven by emerging technologies such as artificial intelligence.YKL-40 holds transformative potential in reshaping post-LT care through precision medicine,providing a pathway for better outcomes and improved management of high-risk LT recipients.
文摘Cardiovascular diseases are the leading cause of death,requiring innovative approaches for prevention,diagnosis,and treatment.Personalized medicine customizes interventions according to individual characteristics,with artificial intelligence(AI)playing a key role in analyzing complex data to improve diagnostic accuracy,predict outcomes,and optimize therapies.AI can identify patterns in imaging and biomarkers,facilitating the earlier detection of medical conditions.Wearable devices and health applications facilitate continuous monitoring and personalized care.Emerging fields such as digital Chinese medicine offer additional perspectives by integrating traditional diagnostic principles with modern digital tools,contributing to holistic and individualized cardiovascular care.This study examines the advancements and challenges in personalized cardiovascular medicine,highlighting the need to address issues such as data privacy,algorithmic bias,and accessibility to promote the equitable application of personalized medicine.
基金supported in part by the National Key R&D Program of China under Grant 2024YFE0200700in part by the National Natural Science Foundation of China under Grant 62201504.
文摘Network architectures assisted by Generative Artificial Intelligence(GAI)are envisioned as foundational elements of sixth-generation(6G)communication system.To deliver ubiquitous intelligent services and meet diverse service requirements,6G network architecture should offer personalized services to various mobile devices.Federated learning(FL)with personalized local training,as a privacypreserving machine learning(ML)approach,can be applied to address these challenges.In this paper,we propose a meta-learning-based personalized FL(PFL)method that improves both communication and computation efficiency by utilizing over-the-air computations.Its“pretraining-and-fine-tuning”principle makes it particularly suitable for enabling edge nodes to access personalized GAI services while preserving local privacy.Experiment results demonstrate the outperformance and efficacy of the proposed algorithm,and notably indicate enhanced communication efficiency without compromising accuracy.
文摘Objective: To explore the effect of Health Action Process Approach (HAPA) theory in patients with type D personality psoriasis. Methods: A total of 66 patients with type D personality psoriasis admitted to the dermatology department of a top-three hospital in Jingzhou City from November 2022 to July 2023 were selected and divided into control group and test group with 33 cases in each group by random number table method. The control group received routine health education, and the experimental group received health education based on the HAPA theory. Chronic disease self-efficacy scale, hospital anxiety and depression scale and skin disease quality of life scale were used to evaluate the effect of intervention. Results: After 3 months of intervention, the scores of self-efficacy in experimental group were higher than those in control group (P P Conclusion: Health education based on the theory of HAPA can enhance the self-efficacy of patients with type D personality psoriasis, relieve negative emotions and improve their quality of life.
文摘Objective:The combination of science and art in nursing is essential for providing effective care.Since art is inherent and a part of human personality traits,it is believed that nurses’personality traits are important to achieve this cohesive combination in nursing.Accordingly,this study was conducted to determine the relationship between nurses’personality traits and the esthetics of nursing care.Methods:A cross-sectional descriptive design was employed.Study participants that consisted of 95 nurses and 285 patients from health centers in Iran were selected by convenience sampling method.Measures included the five-factor personality questionnaires(NEO-FFI)scale and Esthetics of Nursing Care Scale(ENCS).Results:The findings indicated a significant relationship between neuroticism(r=−0.149,P=0.028)and extraversion traits(r=0.136,P=0.045)of nurses in esthetics nursing care.In this study,no significant relationship was found between the personality traits and esthetics of nursing care using nurses’demographic information.Conclusions:The esthetics of nursing care depends on nurse personality traits.Since the art of nursing complements the expected care,it is suggested that nursing managers pay attention to the personality traits of nurses in planning to provide effective care.
基金supported by the major science and technology special projects of Xinjiang(No.2024B03041)the scientific and technological projects of Kashgar(No.KS2024024).
文摘The requirement for precise detection and recognition of target pedestrians in unprocessed real-world imagery drives the formulation of person search as an integrated technological framework that unifies pedestrian detection and person re-identification(Re-ID).However,the inherent discrepancy between the optimization objectives of coarse-grained localization in pedestrian detection and fine-grained discriminative learning in Re-ID,combined with the substantial performance degradation of Re-ID during joint training caused by the Faster R-CNN-based branch,collectively constitutes a critical bottleneck for person search.In this work,we propose a cascaded person searchmodel(SeqXt)based on SeqNet and ConvNeXt that adopts a sequential end-to-end network as its core architecture,artfully integrates the design logic of the two-stepmethod and one-step method framework,and concurrently incorporates the two-step method’s advantage in efficient subtask handling while preserving the one-step method’s efficiency in end-toend training.Firstly,we utilize ConvNeXt-Base as the feature extraction module,which incorporates part of the design concept of Transformer,enhances the consideration of global context information,and boosts feature discrimination through an implicit self-attention mechanism.Secondly,we introduce prototype-guided normalization for calibrating the feature distribution,which leverages the archetype features of individual identities to calibrate the feature distribution and thereby prevents features from being overly inclined towards frequently occurring IDs,notably improving the intra-class compactness and inter-class separability of person identities.Finally,we put forward an innovative loss function named the Dynamic Online Instance Matching Loss Function(DOIM),which employs the hard sample assistantmethod to adaptively update the lookup table(LUT)and the circular queue(CQ)and aims to further enhance the distinctiveness of features between classes.Experimental results on the public datasets CUHK-SYSU and PRWand the private dataset UESTC-PS show that the proposed method achieves state-of-the-art results.
文摘This study investigated the political,economic,social,and cultural environment perceptions on international students that define their acculturation and health related quality of life.Participants were 117 international students from 32 countries attending a Chinese university(females=43%,mean age=21.17 years,SD=4.45 years).They reported on their acculturation to China and physical and psychological well-being.Results from t-tests and correlation analyses indicate political liberals had more positive attitudes toward China than the conservatives,and higher self-reported physical and psychological results.Higher scores on the“interdependence”dimension of self-construal,as well as the“extraversion”and“emotional stability”dimensions of personality traits,were associated with more positive views of China and better health outcomes.These findings are consistent with Berry’s framework for acculturation,which posits that individual-level variables are related to cultural adaptation,and that cultural adaptation is associated with improved physical and mental health.International student offices at host universities should implement comprehensive support programs,including language assistance,cultural orientation,and social integration initiatives to effectively enhance the health related quality of life of international students.
文摘Personalized nursing is a necessary means to improve the satisfaction of emergency pediatric nursing.It can enhance the responsiveness of nursing services,strengthen the emotional connection between nurses and patients,and provide a theoretical basis for clinical practice.Therefore,in the context of the new era,it is necessary to deeply analyze the essence and connotation of personalized nursing,and analyze the existing deficiencies in current emergency pediatric personalized nursing,so as to develop effective improvement plans.Research shows that personalized nursing can significantly improve the satisfaction of emergency pediatric nursing,largely avoid nursing risks,and has strong clinical application value.This article summarizes and explores the research on the influence of personalized nursing on improving the satisfaction of emergency pediatric nursing,and puts forward corresponding views.
文摘Social media outlets deliver customers a medium for communication,exchange,and expression of their thoughts with others.The advent of social networks and the fast escalation of the quantity of data have created opportunities for textual evaluation.Utilising the user corpus,characteristics of social platform users,and other data,academic research may accurately discern the personality traits of users.This research examines the traits of consumer personalities.Usually,personality tests administered by psychological experts via interviews or self-report questionnaires are costly,time-consuming,complex,and labour-intensive.Currently,academics in computational linguistics are increasingly focused on predicting personality traits from social media data.An individual’s personality comprises their traits and behavioral habits.To address this distinction,we propose a novel LSTMapproach(BERT-LIWC-LSTM)that simultaneously incorporates users’enduring and immediate personality characteristics for textual personality recognition.Long-termPersonality Encoding in the proposed paradigmcaptures and represents persisting personality traits.Short-termPersonality Capturing records changing personality states.Experimental results demonstrate that the designed BERT-LIWC-LSTM model achieves an average improvement in accuracy of 3.41% on the Big Five dataset compared to current methods,thereby justifying the efficacy of encoding both stable and dynamic personality traits simultaneously through long-and short-term feature interaction.
基金supported by the Young Doctoral Research Initiation Fund Project of Harbin University“Research on Wood Recognition Methods Based on Deep Learning Fusion Model”(Project no.HUDF2022110)the Self-Funded Project of Harbin Science and Technology Plan“Research on Computer Vision Recognition Technology of Wood Species Based on Transfer Learning FusionModel”(Project no.ZC2022ZJ010027)the Fundamental Research Funds for the Central Universities(2572017PZ10).
文摘Changing a person’s posture and low resolution are the key challenges for person re-identification(ReID)in various deep learning applications.In this paper,we introduce an innovative architecture using a dual attention network that includes an attentionmodule and a joint measurement module of spatial-temporal information.The proposed approach can be classified into two main tasks.Firstly,the spatial attention feature map is formed by aggregating features in the spatial dimension.Additionally,the same operation is carried out on the channel dimension to formchannel attention featuremaps.Therefore,the receptive field size is adjusted adaptively tomitigate the changing person posture issue.Secondly,we use a joint measurement method for the spatial-temporal information to fully harness the data,and it can also naturally integrate the information into the visual features of supervised ReID and hence overcome the low resolution problem.The experimental results indicate that our proposed algorithm markedly improves the accuracy in addressing changing human postures and low-resolution issues compared with contemporary leading techniques.The proposed method shows superior outcomes on widely recognized benchmarks,which are the Market-1501,MSMT17,and DukeMTMC-reID datasets.Furthermore,the proposed algorithmattains a Rank-1 accuracy of 97.4% and 94.9% mAP(mean Average Precision)on the Market-1501 dataset.Moreover,it achieves a 94.2% Rank-1 accuracy and 91.8% mAP on the DukeMTMC-reID dataset.
文摘Diabetes mellitus(DM)comprises distinct subtypes-including type 1 DM,type 2 DM,and gestational DM-all characterized by chronic hyperglycemia and sub-stantial morbidity.Conventional diagnostic and therapeutic strategies often fall short in addressing the complex,multifactorial nature of DM.This review ex-plores how multi-omics integration enhances our mechanistic understanding of DM and informs emerging personalized therapeutic approaches.We consolidated genomic,transcriptomic,proteomic,metabolomic,and microbiomic data from major databases and peer-reviewed publications(2015-2025),with an emphasis on clinical relevance.Multi-omics investigations have identified convergent mole-cular networks underlyingβ-cell dysfunction,insulin resistance,and diabetic complications.The combination of metabolomics and microbiomics highlights critical interactions between metabolic intermediates and gut dysbiosis.Novel biomarkers facilitate early detection of DM and its complications,while single-cell multi-omics and machine learning further refine risk stratification.By dissecting DM heterogeneity more precisely,multi-omics integration enables targeted in-terventions and preventive strategies.Future efforts should focus on data har-monization,ethical considerations,and real-world validation to fully leverage multi-omics in addressing the global DM burden.
文摘Objective:To investigate the distribution of health literacy(HL)levels and the association of HL with proactive personality in patients with permanent colostomy.Methods:A cross-sectional study was conducted to measure proactive personality and HL using validated scales.A total of 172 patients with permanent colostomy were selected from January 2021 to May 2022 in Yantai City,China.Descriptive statistics,t-test,ANOVA,Pearson correlation analysis,and multiple linear regression analysis techniques were used.Results:The results obtained from the study showed that the HL status of the participants was moderate.The correlation between participants’total HL scores and proactive personality scores was 0.417(P-value<0.001).In addition,HL showed statistically significant differences according to education level,place of residence,profession,and average monthly household income.Conclusions:This study showed that patients with higher proactive personality scores had higher HL.The key stakeholders require several positive strategies to improve the HL of patients with permanent colostomy by cultivating their proactive personalities,and these important policies will help to improve patient health and quality of life.
