With the intensifying aging population,rural elderly care services are facing challenges such as uneven medical resources and inadequate facilities.Taking Qinhuangdao City as an example,this paper explores ways to imp...With the intensifying aging population,rural elderly care services are facing challenges such as uneven medical resources and inadequate facilities.Taking Qinhuangdao City as an example,this paper explores ways to improve rural elderly care services through the construction of a remote medical service network.This paper analyzes the current status of rural elderly care services in Qinhuangdao City,pointing out that issues such as the uneven distribution of medical resources between urban and rural areas,poor accessibility,and low service quality urgently need to be addressed.The necessity of accelerating the construction of a remote medical network is proposed,including reducing medical costs,optimizing resource allocation,and disease prevention.Specific measures cover aspects such as policy support,integration of medical and elderly care services,talent cultivation,and technology promotion.At the same time,the potential challenges and risks faced by the remote medical service network in improving rural elderly care services are evaluated,and corresponding countermeasures and suggestions are proposed.Research shows that remote medical care can effectively improve the quality of rural elderly care services and help achieve proper medical care for the elderly.展开更多
In this editorial,we comment on the article by Wang and Long,published in a recent issue of the World Journal of Clinical Cases.The article addresses the challenge of predicting intensive care unit-acquired weakness(I...In this editorial,we comment on the article by Wang and Long,published in a recent issue of the World Journal of Clinical Cases.The article addresses the challenge of predicting intensive care unit-acquired weakness(ICUAW),a neuromuscular disorder affecting critically ill patients,by employing a novel processing strategy based on repeated machine learning.The editorial presents a dataset comprising clinical,demographic,and laboratory variables from intensive care unit(ICU)patients and employs a multilayer perceptron neural network model to predict ICUAW.The authors also performed a feature importance analysis to identify the most relevant risk factors for ICUAW.This editorial contributes to the growing body of literature on predictive modeling in critical care,offering insights into the potential of machine learning approaches to improve patient outcomes and guide clinical decision-making in the ICU setting.展开更多
Improving maternal health is one of the Sustainable Development Goals.Hospital service areas(HSAs),which contain most hospitalization behaviors at the local scale,are crucial for health care planning.However,little at...Improving maternal health is one of the Sustainable Development Goals.Hospital service areas(HSAs),which contain most hospitalization behaviors at the local scale,are crucial for health care planning.However,little attention has been given to HSAs for maternal care and the hierarchy structure.Considering Hubei,central China,as a case study,this study aims to fill these gaps by developing a method for delineating hierarchical HSAs for maternal care using a network optimization approach.The approach is driven by actual patient flow data and has an explicit objective to maximize the modularity.It also establishes the hierarchical structure of maternal care HSAs,which is fundamental for the planning of hierarchical maternal care and referral systems.In our case study,45 secondary HSAs and 22tertiary HSAs are delineated to achieve maximal modularity.The HSAs perform well in terms of indices such as the Localization Index and Market Share Index.Furthermore,there is a complementary relationship between secondary and tertiary hospitals,which suggests the need for referral system planning.This study can provide evidence for the validity of the HSA and the planning of maternal care HSAs in China.It also provides transferable methods for planning hierarchical HSAs in other developing countries.展开更多
Objective: To evaluate the organizational model of a perinatal network and its relevance in a resource-limited country. Methodology: This was a mixed prospective qualitative and quantitative study conducted over a 2-y...Objective: To evaluate the organizational model of a perinatal network and its relevance in a resource-limited country. Methodology: This was a mixed prospective qualitative and quantitative study conducted over a 2-year period, from January 1, 2022, to December 31, 2023. This study took place in Senegal, a country with limited resources and a weakness of hyperspecialized medical technical resources. There was no policy for the management of fetal malformations. The qualitative part was carried out through overt participant observation. The human resources and the organization of the perinatal network were described. For the quantitative part, all fetuses managed during the study period were included. The studied parameters related to neonatal care and outcomes. Qualitative variables were described using dispersion parameters, and quantitative variables were described using proportions. Results: The perinatal network includes several specialists across six hospitals. Of these hospitals, only one provided emergency pediatric surgery. The network included highly specialized human resources in prenatal diagnosis, congenital heart defects, pediatric surgery, anesthesia, and other medical specialties in perinatology. Advanced ultrasound was centralized by an obstetrician. The team decided on the follow-up methods, timing, and mode of delivery. The newborn was immediately transferred to the appropriate specialty. Over the 2-year period, 201 fetuses were managed. The rate of cesarean delivery was 76.3%. Neonatal mortality was 51.4%. Discussion: Centralizing care improves the quality of prenatal diagnosis and management of congenital defects. Mortality remains high when emergency surgery is not well available. This mortality is also due to the lack of a single center offering all perinatal care and so, the transfer of newborns. The cesarean rate increases due to underlying conditions and organizational factors. Conclusion: Public policies should prioritize the centralization of care for congenital disorders to reduce the costs of disability and mortality.展开更多
With the increasing demand for high reliability and availability in power conversion equipment within power electronics systems,the fault diagnosis of neutral-point-clamped(NPC) three-level inverters has garnered wide...With the increasing demand for high reliability and availability in power conversion equipment within power electronics systems,the fault diagnosis of neutral-point-clamped(NPC) three-level inverters has garnered widespread attention.To address the challenges of fault feature extraction,this article proposes an end-to-end diagnostic approach based on a wavelet kernel convolutional neural network (WKCNN),capable of extracting multi-scale features from current signals to significantly enhance diagnostic accuracy.This method directly uses raw three-phase current signals as input,applying wavelet kernel convolution to automatically capture frequency-domain fault features,combined with a Softmax classifier optimized by the Adam algorithm to achieve fault diagnosis for NPC threelevel inverters.Experimental results under various operating conditions demonstrate that this approach maintains robust diagnostic accuracy across multiple fault scenarios,with comparative analysis further confirming its advantages in diagnostic efficiency and performance over traditional machine learning and other deep learning methods.展开更多
目的探讨不同口腔护理方法对新生儿呼吸机相关性肺炎预防效果。方法检索PubMed、Embase、Cochrane Library、Web of Science、中国知网、万方、维普和中国生物医学文献数据库中不同口腔护理方法对新生儿呼吸机相关性肺炎预防效果的随机...目的探讨不同口腔护理方法对新生儿呼吸机相关性肺炎预防效果。方法检索PubMed、Embase、Cochrane Library、Web of Science、中国知网、万方、维普和中国生物医学文献数据库中不同口腔护理方法对新生儿呼吸机相关性肺炎预防效果的随机对照试验,检索时限均为建库至2025年2月。由2名研究员独立进行文献筛查、数据提取、质量评价,对符合纳排标准的文献采用Stata 15.1软件进行数据分析。结果共纳入24篇文献,涉及7种口腔护理方法,包括2.0%或2.5%碳酸氢钠溶液(以下简称“碳酸氢钠溶液”)擦拭、母乳擦拭、碳酸氢钠溶液联合母乳擦拭、生理盐水擦拭、碳酸氢钠溶液联合过氧化氢溶液擦拭、碳酸氢钠溶液擦拭联合生理盐水冲洗、无菌水擦拭。网状Meta分析显示,不同口腔护理方法预防新生儿呼吸机相关性肺炎效果不同,效果最好的是碳酸氢钠溶液擦拭联合生理盐水冲洗、碳酸氢钠溶液联合过氧化氢溶液擦拭及碳酸氢钠溶液联合母乳擦拭,其他方式效果略差。结论当前有限证据显示,碳酸氢钠溶液擦拭联合生理盐水冲洗是预防新生儿呼吸机相关性肺炎的有效口腔护理方法之一,其次是碳酸氢钠溶液联合过氧化氢溶液擦拭、碳酸氢钠溶液联合母乳擦拭、母乳擦拭、无菌水擦拭,碳酸氢钠溶液擦拭、生理盐水擦拭的效果排最后。受纳入文献数量和质量的限制,上述结论尚需开展更多高质量研究予以验证。展开更多
Sensor network has experienced world-wide explosive interests in recent years. It combines the technology of modern microelectronic sensors, embedded computational processing systems, and modern computer and wireless ...Sensor network has experienced world-wide explosive interests in recent years. It combines the technology of modern microelectronic sensors, embedded computational processing systems, and modern computer and wireless networking methodologies. In this overview paper, we first provide some rationales for the growth of sensor networking. Then we discuss various basic concepts and hardware issues. Four basic application cases in the US. National Science Foundation funded Ceneter for Embedded Networked Sensing program at UCLA are presented. Finally, six challenging issues in sensor networks are discussed. Numerous references including relevant papers, books, and conferences that have appeared in recent years are given.展开更多
While a large number of studies have described animal social networks, we have a poor understanding of how these networks vary with ecological and social conditions. For example, reproductive periods are an important ...While a large number of studies have described animal social networks, we have a poor understanding of how these networks vary with ecological and social conditions. For example, reproductive periods are an important life-history stage that may involve changes in dominance relationships among individuals, yet no study to date has compared social networks of do- minance interactions （i.e. dominance networks） across reproductive contexts. We first analyzed a long-term dataset on captive so- cial groups of the cooperatively breeding cichlid Neolamprologuspulcher, and found that eviction events were significantly more common around reproduction than expected by chance. Next, we compared the structure of dominance networks during early pa- rental care and non-reproductive periods, using one of the first applications of exponential random graph models in behavioral biology. Contrary to our predictions, we found that dominance networks showed few changes between early parental care and non-reproductive periods. We found no evidence that dominance interactions became more skewed towards larger individuals, became more frequent between similar-sized individuals, or became more biased towards a particular sex during parental care. However, we did find that there were relatively more dominance interactions between opposite-sex dyads in the early parental care period, which may be a by-product of increased sexual interactions during this time. This is the first study in behavioral ecology to compare social networks using exponential random graph modeling, and demonstrates a powerful analytical framework for future studies in the field [Current Zoology 61 （1）： 45-54, 2015].展开更多
Recent developments of the wireless sensor network will revolutionize the way of remote monitoring in dif-ferent domains such as smart home and smart care, particularly remote cardiac care. Thus, it is challenging to ...Recent developments of the wireless sensor network will revolutionize the way of remote monitoring in dif-ferent domains such as smart home and smart care, particularly remote cardiac care. Thus, it is challenging to propose an energy efficient technique for automatic ECG diagnosis (AED) to be embedded into the wireless sensor. Due to the high resource requirements, classical AED methods are unsuitable for pervasive cardiac care (PCC) applications. This paper proposes an embedded real-time AED algorithm dedicated to PCC sys-tems. This AED algorithm consists of a QRS detector and a rhythm classifier. The QRS detector adopts the linear time-domain statistical and syntactic analysis method and the geometric feature extraction modeling technique. The rhythm classifier employs the self-learning expert system and the confidence interval method. Currently, this AED algorithm has been implemented and evaluated on the PCC system for 30 patients in the Gabriel Monpied hospital (CHRU of Clermont-Ferrand, France) and the MIT-BIH cardiac arrhythmias da-tabase. The overall results show that this energy efficient algorithm provides the same performance as the classical ones.展开更多
Relatively soon after their accident, patients suffering a spinal cord injury(SCI) begin generally experiencing the development of significant, often life-threatening secondary complications. Many of which are associa...Relatively soon after their accident, patients suffering a spinal cord injury(SCI) begin generally experiencing the development of significant, often life-threatening secondary complications. Many of which are associated with chronic physical inactivity-related immune function problems and increasing susceptibility to infection that repeatedly requires intensive care treatment. Therapies capable of repairing the spinal cord or restoring ambulation would normally prevent many of these problems but, as of now, there is no cure for SCI. Thus, management strategies and antibiotics remain the standard of care although antimicrobial resistance constitutes a significant challenge for patients with chronic SCI facing recurrent infections of the urinary tract and respiratory systems. Identifying alternative therapies capable of safe and potent actions upon these serious health concerns should therefore be considered a priority. This editorial presents some of the novel approaches currently in development for the prevention of specific infections after SCI. Among them, brain-permeable small molecule therapeutics acting centrally on spinal cord circuits that can augment respiratory capabilities or bladder functions. If eventually approved by regulatory authorities, some of these new avenues may potentially become clinically-relevant therapies capable of indirectly preventing the occurrence and/or severity of these lifethreatening complications in people with paraplegic or tetraplegic injuries.展开更多
In this editorial,we discuss an article titled,“Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning,”published in a recent issue of the World J...In this editorial,we discuss an article titled,“Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning,”published in a recent issue of the World Journal of Clinical Cases.Intensive care unit-acquired weakness(ICU-AW)is a debilitating condition that affects critically ill patients,with significant implications for patient outcomes and their quality of life.This study explored the use of artificial intelligence and machine learning techniques to predict ICU-AW occurrence and identify key risk factors.Data from a cohort of 1063 adult intensive care unit(ICU)patients were analyzed,with a particular emphasis on variables such as duration of ICU stay,duration of mechanical ventilation,doses of sedatives and vasopressors,and underlying comorbidities.A multilayer perceptron neural network model was developed,which exhibited a remarkable impressive prediction accuracy of 86.2%on the training set and 85.5%on the test set.The study highlights the importance of early prediction and intervention in mitigating ICU-AW risk and improving patient outcomes.展开更多
文摘With the intensifying aging population,rural elderly care services are facing challenges such as uneven medical resources and inadequate facilities.Taking Qinhuangdao City as an example,this paper explores ways to improve rural elderly care services through the construction of a remote medical service network.This paper analyzes the current status of rural elderly care services in Qinhuangdao City,pointing out that issues such as the uneven distribution of medical resources between urban and rural areas,poor accessibility,and low service quality urgently need to be addressed.The necessity of accelerating the construction of a remote medical network is proposed,including reducing medical costs,optimizing resource allocation,and disease prevention.Specific measures cover aspects such as policy support,integration of medical and elderly care services,talent cultivation,and technology promotion.At the same time,the potential challenges and risks faced by the remote medical service network in improving rural elderly care services are evaluated,and corresponding countermeasures and suggestions are proposed.Research shows that remote medical care can effectively improve the quality of rural elderly care services and help achieve proper medical care for the elderly.
文摘In this editorial,we comment on the article by Wang and Long,published in a recent issue of the World Journal of Clinical Cases.The article addresses the challenge of predicting intensive care unit-acquired weakness(ICUAW),a neuromuscular disorder affecting critically ill patients,by employing a novel processing strategy based on repeated machine learning.The editorial presents a dataset comprising clinical,demographic,and laboratory variables from intensive care unit(ICU)patients and employs a multilayer perceptron neural network model to predict ICUAW.The authors also performed a feature importance analysis to identify the most relevant risk factors for ICUAW.This editorial contributes to the growing body of literature on predictive modeling in critical care,offering insights into the potential of machine learning approaches to improve patient outcomes and guide clinical decision-making in the ICU setting.
基金National Natural Science Foundation of China,No.41671497。
文摘Improving maternal health is one of the Sustainable Development Goals.Hospital service areas(HSAs),which contain most hospitalization behaviors at the local scale,are crucial for health care planning.However,little attention has been given to HSAs for maternal care and the hierarchy structure.Considering Hubei,central China,as a case study,this study aims to fill these gaps by developing a method for delineating hierarchical HSAs for maternal care using a network optimization approach.The approach is driven by actual patient flow data and has an explicit objective to maximize the modularity.It also establishes the hierarchical structure of maternal care HSAs,which is fundamental for the planning of hierarchical maternal care and referral systems.In our case study,45 secondary HSAs and 22tertiary HSAs are delineated to achieve maximal modularity.The HSAs perform well in terms of indices such as the Localization Index and Market Share Index.Furthermore,there is a complementary relationship between secondary and tertiary hospitals,which suggests the need for referral system planning.This study can provide evidence for the validity of the HSA and the planning of maternal care HSAs in China.It also provides transferable methods for planning hierarchical HSAs in other developing countries.
文摘Objective: To evaluate the organizational model of a perinatal network and its relevance in a resource-limited country. Methodology: This was a mixed prospective qualitative and quantitative study conducted over a 2-year period, from January 1, 2022, to December 31, 2023. This study took place in Senegal, a country with limited resources and a weakness of hyperspecialized medical technical resources. There was no policy for the management of fetal malformations. The qualitative part was carried out through overt participant observation. The human resources and the organization of the perinatal network were described. For the quantitative part, all fetuses managed during the study period were included. The studied parameters related to neonatal care and outcomes. Qualitative variables were described using dispersion parameters, and quantitative variables were described using proportions. Results: The perinatal network includes several specialists across six hospitals. Of these hospitals, only one provided emergency pediatric surgery. The network included highly specialized human resources in prenatal diagnosis, congenital heart defects, pediatric surgery, anesthesia, and other medical specialties in perinatology. Advanced ultrasound was centralized by an obstetrician. The team decided on the follow-up methods, timing, and mode of delivery. The newborn was immediately transferred to the appropriate specialty. Over the 2-year period, 201 fetuses were managed. The rate of cesarean delivery was 76.3%. Neonatal mortality was 51.4%. Discussion: Centralizing care improves the quality of prenatal diagnosis and management of congenital defects. Mortality remains high when emergency surgery is not well available. This mortality is also due to the lack of a single center offering all perinatal care and so, the transfer of newborns. The cesarean rate increases due to underlying conditions and organizational factors. Conclusion: Public policies should prioritize the centralization of care for congenital disorders to reduce the costs of disability and mortality.
基金supported in part by Zhejiang Provincial“Pioneer”and“Leading Goose”R&D Program of China under Grant 2024C01014the National Natural Science Foundation of China under Grant52177055。
文摘With the increasing demand for high reliability and availability in power conversion equipment within power electronics systems,the fault diagnosis of neutral-point-clamped(NPC) three-level inverters has garnered widespread attention.To address the challenges of fault feature extraction,this article proposes an end-to-end diagnostic approach based on a wavelet kernel convolutional neural network (WKCNN),capable of extracting multi-scale features from current signals to significantly enhance diagnostic accuracy.This method directly uses raw three-phase current signals as input,applying wavelet kernel convolution to automatically capture frequency-domain fault features,combined with a Softmax classifier optimized by the Adam algorithm to achieve fault diagnosis for NPC threelevel inverters.Experimental results under various operating conditions demonstrate that this approach maintains robust diagnostic accuracy across multiple fault scenarios,with comparative analysis further confirming its advantages in diagnostic efficiency and performance over traditional machine learning and other deep learning methods.
文摘目的探讨不同口腔护理方法对新生儿呼吸机相关性肺炎预防效果。方法检索PubMed、Embase、Cochrane Library、Web of Science、中国知网、万方、维普和中国生物医学文献数据库中不同口腔护理方法对新生儿呼吸机相关性肺炎预防效果的随机对照试验,检索时限均为建库至2025年2月。由2名研究员独立进行文献筛查、数据提取、质量评价,对符合纳排标准的文献采用Stata 15.1软件进行数据分析。结果共纳入24篇文献,涉及7种口腔护理方法,包括2.0%或2.5%碳酸氢钠溶液(以下简称“碳酸氢钠溶液”)擦拭、母乳擦拭、碳酸氢钠溶液联合母乳擦拭、生理盐水擦拭、碳酸氢钠溶液联合过氧化氢溶液擦拭、碳酸氢钠溶液擦拭联合生理盐水冲洗、无菌水擦拭。网状Meta分析显示,不同口腔护理方法预防新生儿呼吸机相关性肺炎效果不同,效果最好的是碳酸氢钠溶液擦拭联合生理盐水冲洗、碳酸氢钠溶液联合过氧化氢溶液擦拭及碳酸氢钠溶液联合母乳擦拭,其他方式效果略差。结论当前有限证据显示,碳酸氢钠溶液擦拭联合生理盐水冲洗是预防新生儿呼吸机相关性肺炎的有效口腔护理方法之一,其次是碳酸氢钠溶液联合过氧化氢溶液擦拭、碳酸氢钠溶液联合母乳擦拭、母乳擦拭、无菌水擦拭,碳酸氢钠溶液擦拭、生理盐水擦拭的效果排最后。受纳入文献数量和质量的限制,上述结论尚需开展更多高质量研究予以验证。
基金Supported by the US National Science Foundation, Center for Embedded Networked Sensing (EF-0410438) ARO-Multidisciplinary University Research Initiative/Penn State University (50126) in the USA
文摘Sensor network has experienced world-wide explosive interests in recent years. It combines the technology of modern microelectronic sensors, embedded computational processing systems, and modern computer and wireless networking methodologies. In this overview paper, we first provide some rationales for the growth of sensor networking. Then we discuss various basic concepts and hardware issues. Four basic application cases in the US. National Science Foundation funded Ceneter for Embedded Networked Sensing program at UCLA are presented. Finally, six challenging issues in sensor networks are discussed. Numerous references including relevant papers, books, and conferences that have appeared in recent years are given.
文摘While a large number of studies have described animal social networks, we have a poor understanding of how these networks vary with ecological and social conditions. For example, reproductive periods are an important life-history stage that may involve changes in dominance relationships among individuals, yet no study to date has compared social networks of do- minance interactions （i.e. dominance networks） across reproductive contexts. We first analyzed a long-term dataset on captive so- cial groups of the cooperatively breeding cichlid Neolamprologuspulcher, and found that eviction events were significantly more common around reproduction than expected by chance. Next, we compared the structure of dominance networks during early pa- rental care and non-reproductive periods, using one of the first applications of exponential random graph models in behavioral biology. Contrary to our predictions, we found that dominance networks showed few changes between early parental care and non-reproductive periods. We found no evidence that dominance interactions became more skewed towards larger individuals, became more frequent between similar-sized individuals, or became more biased towards a particular sex during parental care. However, we did find that there were relatively more dominance interactions between opposite-sex dyads in the early parental care period, which may be a by-product of increased sexual interactions during this time. This is the first study in behavioral ecology to compare social networks using exponential random graph modeling, and demonstrates a powerful analytical framework for future studies in the field [Current Zoology 61 （1）： 45-54, 2015].
文摘Recent developments of the wireless sensor network will revolutionize the way of remote monitoring in dif-ferent domains such as smart home and smart care, particularly remote cardiac care. Thus, it is challenging to propose an energy efficient technique for automatic ECG diagnosis (AED) to be embedded into the wireless sensor. Due to the high resource requirements, classical AED methods are unsuitable for pervasive cardiac care (PCC) applications. This paper proposes an embedded real-time AED algorithm dedicated to PCC sys-tems. This AED algorithm consists of a QRS detector and a rhythm classifier. The QRS detector adopts the linear time-domain statistical and syntactic analysis method and the geometric feature extraction modeling technique. The rhythm classifier employs the self-learning expert system and the confidence interval method. Currently, this AED algorithm has been implemented and evaluated on the PCC system for 30 patients in the Gabriel Monpied hospital (CHRU of Clermont-Ferrand, France) and the MIT-BIH cardiac arrhythmias da-tabase. The overall results show that this energy efficient algorithm provides the same performance as the classical ones.
文摘Relatively soon after their accident, patients suffering a spinal cord injury(SCI) begin generally experiencing the development of significant, often life-threatening secondary complications. Many of which are associated with chronic physical inactivity-related immune function problems and increasing susceptibility to infection that repeatedly requires intensive care treatment. Therapies capable of repairing the spinal cord or restoring ambulation would normally prevent many of these problems but, as of now, there is no cure for SCI. Thus, management strategies and antibiotics remain the standard of care although antimicrobial resistance constitutes a significant challenge for patients with chronic SCI facing recurrent infections of the urinary tract and respiratory systems. Identifying alternative therapies capable of safe and potent actions upon these serious health concerns should therefore be considered a priority. This editorial presents some of the novel approaches currently in development for the prevention of specific infections after SCI. Among them, brain-permeable small molecule therapeutics acting centrally on spinal cord circuits that can augment respiratory capabilities or bladder functions. If eventually approved by regulatory authorities, some of these new avenues may potentially become clinically-relevant therapies capable of indirectly preventing the occurrence and/or severity of these lifethreatening complications in people with paraplegic or tetraplegic injuries.
基金Supported by China Medical University,No.CMU111-MF-102.
文摘In this editorial,we discuss an article titled,“Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning,”published in a recent issue of the World Journal of Clinical Cases.Intensive care unit-acquired weakness(ICU-AW)is a debilitating condition that affects critically ill patients,with significant implications for patient outcomes and their quality of life.This study explored the use of artificial intelligence and machine learning techniques to predict ICU-AW occurrence and identify key risk factors.Data from a cohort of 1063 adult intensive care unit(ICU)patients were analyzed,with a particular emphasis on variables such as duration of ICU stay,duration of mechanical ventilation,doses of sedatives and vasopressors,and underlying comorbidities.A multilayer perceptron neural network model was developed,which exhibited a remarkable impressive prediction accuracy of 86.2%on the training set and 85.5%on the test set.The study highlights the importance of early prediction and intervention in mitigating ICU-AW risk and improving patient outcomes.
