*Correspondence on "Large language models can support generation of standardized discharge summaries - A retrospective study utilizing ChatGPT-4 and electronic health records" [0.03%]
关于“大型语言模型可以支持生成标准出院总结——一项回顾性研究，利用ChatGPT-4和电子健康记录”的评论
Amnuay Kleebayoon,Viroj Wiwanitkit
Amnuay Kleebayoon
Development of machine learning-based models to predict congenital heart disease: A matched case-control study [0.03%]
基于机器学习的先天性心脏病预测模型的发展：一项匹配病例对照研究
Shutong Zhang,Chenxi Kang,Jing Cui et al.
Shutong Zhang et al.
Background: The current congenital heart disease (CHD) prediction tools lack adequate interpretability and convenience, hindering the development of personalized CHD management strategies. We developed a machine learning-...
Association of clerical burden and EHR frustration with burnout and career intentions among physician faculty in an urban academic health system [0.03%]
城市学术医疗体系中文书负担和电子健康档案(EHR)挫败感与医师教职工的职业倦怠及职业意向的相关性研究
Jonathan A Ripp,Robert H Pietrzak,Eleonore de Guillebon et al.
Jonathan A Ripp et al.
Background and objectives: To examine changes in clerical burden, including daily clerical time, daily after hours Electronic Health Record (EHR) time and EHR frustration between 2018 and 2022 among physician faculty, and...
Application of machine learning for delirium prediction and analysis of associated factors in hospitalized COVID-19 patients: A comparative study using the Korean Multidisciplinary cohort for delirium prevention (KoMCoDe) [0.03%]
机器学习在住院COVID-19患者谵妄预测及危险因素分析中的应用：韩国多学科预防谵妄队列（KoMCoDe）的比较研究
Hye Yoon Park,Hyoju Sohn,Arum Hong et al.
Hye Yoon Park et al.
Background: The incidence of delirium in hospitalized coronavirus disease 2019 (COVID-19) patients is linked to adverse health outcomes. Predicting the occurrence and risk factors of delirium is key to preventing its sudd...
Construction and evaluation of prediction model for postoperative re-fractures in elderly patients with hip fractures [0.03%]
老年股骨骨折术后再骨折的预测模型构建及评价
Jingjing Wu,Qingqing Zeng,Sijie Gui et al.
Jingjing Wu et al.
Objective: The aim of study was to construct a postoperative re-fracture prediction model for elderly hip fracture patients using an automated machine learning algorithm to provide a basis for early identification of pati...
Jingkai Ruan,Qianmin Su,Zihang Chen et al.
Jingkai Ruan et al.
Background: As fundamental documents in clinical trials, clinical trial protocols are intended to ensure that trials are conducted according to the objectives set by researchers. The advent of large models with superior s...
Corrigendum to "Application of the openEHR reference model for PGHD: A case study on the DH-Convener initiative" [Int. J. Med. Inf. 193 (2025) 105686] [0.03%]
“开放EHR参考模型在PGHD中的应用：DH-Convener倡议案列研究”一文的勘误表
Somayeh Abedian,Sten Hanke,Rada Hussein
Somayeh Abedian
Towards a Multi-Stakeholder process for developing responsible AI governance in consumer health [0.03%]
迈向消费者健康负责任的AI治理的多利益相关者过程
Leon Rozenblit,Amy Price,Anthony Solomonides et al.
Leon Rozenblit et al.
Introduction: AI is big and moving fast into healthcare, creating opportunities and risks. However, current approaches to governance focus on high-level principles rather than tailored recommendations for specific domains...
Prediction of mortality in hemodialysis patients based on autoencoders [0.03%]
基于自动编码器的血液透析患者死亡率预测模型
Shuzhi Su,Jisheng Gao,Jingjing Dong et al.
Shuzhi Su et al.
Background: Patients with end-stage renal disease (ESRD) undergoing hemodialysis (HD) exhibit a high mortality risk, particularly at the onset of treatment. Conventional risk assessment models, dependent on extensive temp...
Developing a prototype for federated analysis to enhance privacy and enable trustworthy access to COVID-19 research data [0.03%]
开发一个原型以增强隐私并实现对COVID-19研究数据的可信访问
Solmaz Eradat Oskoui,Matthew Retford,Eoghan Forde et al.
Solmaz Eradat Oskoui et al.
Background: The use of federated networks can reduce the risk of disclosure for sensitive datasets by removing the requirement to physically transfer data. Federated networks support federated analytics, a type of privacy...