Integrating clinical guidelines with large language models for improved sepsis mortality prediction [0.03%]
结合临床指南的大语义模型在预测脓毒症死亡率方面的应用
Zhen Zhao,Bo An,Tianpeng Zhang et al.
Zhen Zhao et al.
We develop and validate a clinical guideline-integrated LLM for enhanced sepsis mortality prediction. Using MIMIC-IV data from 24,237 ICU sepsis patients, we fine-tuned a large language model with Low-Rank Adaptation, embedding clinical gui...
A robust ensemble-based deep learning framework for automated retinal disease detection [0.03%]
一种鲁棒的基于深度学习的视网膜疾病检测框架
Goldy Verma,Rania M Ghoniem,Sheifali Gupta et al.
Goldy Verma et al.
ObjectiveTo develop a robust deep learning framework for automated multi-class retinal disease detection supporting clinical decision-making, addressing existing models' limitations in generalizability and accuracy.MethodsA novel ensemble m...
An assessment of patient readiness to engage in digital patient reported outcomes in an Australian inflammatory bowel disease cohort [0.03%]
评估澳大利亚炎症性肠病队列中患者参与数字患者报告结果的准备情况
Tsz Hong Yiu,Sarah Rouse,Caitlin Hausler et al.
Tsz Hong Yiu et al.
Objectives: Digital patient-reported outcome (PRO) tools, though beneficial for managing inflammatory bowel disease (IBD), remain underutilized in Australia. This study aimed to investigate a group of Australian patients' readiness to engag...
Joonyoung Park,Eunji Park,Duri Lee et al.
Joonyoung Park et al.
Background: Human Digital Twins (HDTs) have recently emerged, especially in the context of healthcare. With the growing emphasis on preventive healthcare beyond diagnosis, pervasive sensing has become essential which enables continuous moni...
Application of machine learning to identify key factors influencing agricultural workers' mental health: A case study of Thai farmers [0.03%]
机器学习在识别影响农业工作者精神健康的关键因素方面的应用——以泰国农民为例的研究
Papis Wongchaisuwat,Veerasit Kaewbundit,Saisattha Noomnual
Papis Wongchaisuwat
Objectives: This study examined the associations between pesticide exposures, perceived farm stressors, COVID-19-related stressors, and mental health disorders among Thai farmers. Methods: A total of 270 participants were interviewed to ass...
A scoping review of electronic health records interoperability levels, expectations, approaches, and problems [0.03%]
电子健康记录互操作性水平、期望、方法和问题的综述
Raghid El-Yafouri,Leslie Klieb
Raghid El-Yafouri
To achieve useful interoperability between electronic health record (EHR) systems, many approaches have been proposed. To date, none has prevailed as a clear solution. This scoping review studies 24 publications from 2014 to 2023. The aim i...
Quality and readability of chatbot responses to patient questions: A systematic cross-sectional meta-synthesis [0.03%]
聊天机器人回答患者问题的质量和可读性：系统横断面综合分析
Peter Whittaker,Mengyan Sun
Peter Whittaker
Introduction: Patients increasingly use chatbots to obtain medical information, a trend that has provoked both optimism and pessimism. Numerous studies have evaluated the quality and readability of these outputs. This study synthesizes thes...
Predictors of and reasons for refusal to participate in a digitally supported remote maintenance pulmonary rehabilitation programme [0.03%]
影响数字支持的远程维持性肺康复项目参与预测因素及拒绝参与的原因分析
François Alexandre,Virginie Molinier,Espérance Moine et al.
François Alexandre et al.
Objective: The study aimed to assess the predictors and the reasons for refusal to participate in a digitally supported remote maintenance pulmonary rehabilitation programme (M-PRP). Methods: Patients contacted to integrate a 12-month M-PRP...
Using machine learning models to predict coronary artery calcium scores in firefighters [0.03%]
利用机器学习模型预测消防员冠状动脉钙化评分
Mingyue Li,Jiali Han,Carolyn Muegge et al.
Mingyue Li et al.
Objective: To develop and compare the predictive accuracy of machine learning (ML) models for coronary artery calcium (CAC) prediction among firefighters and to evaluate their cross-validated performance against traditional binary logistic ...
Combating health misinformation with fusion-based credible retrieval techniques [0.03%]
基于融合的可信检索技术打击健康谣言
Yidong Huang,Shengli Wu,Hu Lu et al.
Yidong Huang et al.
This study aims to combat health misinformation by enhancing the retrieval of credible health information using effective fusion-based techniques. It focuses on clustering-based subset selection to improve data fusion performance. Five clus...