Evaluating community-based digital health interventions to improve COVID-19 outcomes in rural Indonesia: a quasi-experimental study [0.03%]
在印度尼西亚农村地区评估基于社区的数字健康干预措施以改善COVID-19预后：准实验研究
Sujarwoto Sujarwoto,Holipah Holipah,Sri Andarini et al.
Sujarwoto Sujarwoto et al.
Objectives: COVID-19 has challenged health systems in low-income and middle-income countries, particularly in rural areas where communities face barriers to information, prevention and timely care. Digital health interven...
Examining healthcare inequality for non-communicable diseases in Malawi: a hierarchical geospatial modelling approach [0.03%]
马拉维非传染性疾病医疗不平等性研究：分层地理空间建模方法
Yanjia Cao,Jiashuo Sun,Sali Ahmed et al.
Yanjia Cao et al.
Objectives: The prevalence of non-communicable diseases (NCDs) is rising in low- and middle-income countries, including Malawi, yet spatial inequalities in NCD healthcare coverage remain poorly understood. In this researc...
Exploring factors influencing patient choice in outpatient ophthalmology provider in the North London region: a patient survey [0.03%]
伦敦北部地区眼科门诊医生选择因素分析——基于患者的调查研究
Rishi Ramessur,Roxanne Crosby-Nwaobi,Claire Lovegrove et al.
Rishi Ramessur et al.
Objectives: To explore factors important to patients when choosing a secondary care provider. Methods: A survey was distributed to 376 ...
Digital tumour board solution enhances case preparation time and reduces postponements: an implementer report [0.03%]
一种数字肿瘤委员会解决方案可缩短病例准备时间并减少延期：实施者报告
Katja Brne,Katharina Abraham,Mieke Arnoldus et al.
Katja Brne et al.
Objective: Inefficiencies and high administrative burdens are commonly reported in multidisciplinary tumour boards (TBs). The objective of the study was to evaluate the impact of a digital solution on the common challenge...
Observational Study
BMJ health & care informatics. 2025 Oct 29;32(1):e101332. DOI:10.1136/bmjhci-2024-101332 2025
Effects of nature-based virtual reality interventions on physical and mental health symptoms in patients with cancer undergoing chemotherapy: a systematic review and meta-analysis protocol [0.03%]
基于自然的虚拟现实干预措施对化疗癌症患者的身体和心理健康症状的影响：系统评价和meta分析方案
Surui Liang,Xiaojiao Wang,Jing Jing Su et al.
Surui Liang et al.
Objectives: The study aims to evaluate the effectiveness of nature-based virtual reality (NBVR) interventions in alleviating physical symptoms (eg, pain, fatigue, nausea) and mental symptoms (eg, anxiety, depression, dist...
From words to action? A scoping review on automatic sentiment analysis of patient experience comments from online sources and surveys [0.03%]
从话语到行动？来自线上资源和调查的患者体验评论的自动情感分析的研究综述
Elma Jelin,Lilja Charlotte Storset,Rebecka M Norman et al.
Elma Jelin et al.
Background: Automatic analysis of free-text patient comments enables the efficient processing of large feedback volumes, reducing reliance on manual review. A 2021 review examined natural language processing (NLP) and sen...
Comparing computable type 2 diabetes phenotype definitions in identifying populations of interest for clinical research [0.03%]
比较可计算的2型糖尿病表型定义以识别临床研究感兴趣的群体
Priyanka D Sood,Star Liu,Rita R Kalyani et al.
Priyanka D Sood et al.
Objective: Significant variations exist in computable phenotype definitions to identify patients with type 2 diabetes (T2D) using electronic health records (EHRs). These variations cause challenges in identifying T2D popu...
Comparative Study
BMJ health & care informatics. 2025 Oct 22;32(1):e101378. DOI:10.1136/bmjhci-2024-101378 2025
Rapid discrimination of Mycobacterium tuberculosis and non-tuberculous mycobacteria disease via interpretive machine learning analysis of routine laboratory tests [0.03%]
基于常规实验室检验的解释性机器学习分析鉴别结核分枝杆菌和非结核分枝杆菌感染
Jia-Wei Tang,Xue-Song Xiong,Ting-Ting Huang et al.
Jia-Wei Tang et al.
Objectives: Rapid discrimination of infections caused by Mycobacterium tuberculosis (MTB) and non-tuberculous mycobacteria (NTM) is crucial in clinical settings. Despite overlapping clinical and radiological features, the...
Machine learning predictive system to predict the risk of developing pre-eclampsia [0.03%]
一种预测子痫前期发病风险的机器学习系统
Ing-Luen Shyu,Chung-Feng Liu,Yung-Chieh Tsai et al.
Ing-Luen Shyu et al.
Objectives: To develop a machine learning (ML)-based predictive model for assessing the risk of pre-eclampsia using routinely collected clinical data. Met...
Bridging generative AI and healthcare practice: insights from the GenAI Health Hackathon at Hospital Clínic de Barcelona [0.03%]
连接生成式人工智能与医疗实践：巴塞罗那克利尼克医院GenAI Health黑客松的见解
Santiago Frid,Octavi Bassegoda,Maria Araceli Camacho Mahamud et al.
Santiago Frid et al.
Objectives: To describe the implementation of a multidisciplinary, ethically grounded hackathon as a model to develop and evaluate generative AI (GenAI) solutions for real-world clinical challenges within a hospital setti...