Blepharospasm is a focal dystonia characterized by involuntary eyelid contractions that impair vision and social function. The subtle clinical signs of blepharospasm make early and accurate diagnosis difficult, delaying timely intervention. In this study,…
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This study harnesses machine learning to dissect the complex socioeconomic determinants of depression risk among older adults across five international cohorts (HRS, ELSA, SHARE, CHARLS, MHAS). Evaluating six predictive algorithms, XGBoost demonstrated superior performance…
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For patients with locally advanced cervical cancer (LACC), precise survival prediction models could guide personalized treatment. We developed and validated CerviPro, a deep learning-based multimodal prognostic model, to predict disease-free survival (DFS) in 1018…
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A study from the University of Westminster’s Research Centre for Optimal Health (ReCOH) has developed an AI method to predict the early onset of 38 age-related diseases through analysis of UK Biobank data.
The study,…
Hepatocellular carcinoma (HCC) ultrasound screening encounters challenges related to accuracy and the workload of radiologists. This retrospective, multicenter study assessed four artificial intelligence (AI) enhanced strategies using 21,934 liver ultrasound images from 11,960 patients…
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The evolution of surgical techniques aims to augment surgeons’ capabilities through digital guidance and robotization for higher precision and consistency. Currently, surgeries heavily rely on surgeon’s experience and visual judgment, causing operation variations. Artificial…
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In this study, we review the application of digital technologies for health in China, examining the structure of its digital health governance. China’s digital health governance is of political commitment, cross-sectoral collaboration, and a…
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Engaging patients in the digital collection of electronic patient-reported outcome measures (ePROMs) and experience measures (ePREMs) is desirable for equitable, patient-centred chronic disease management; however, adherence remain unclear. This study examined demographic and socioeconomic…
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Radiology reporting is a time-intensive process, and artificial intelligence (AI) shows potential for textual processing in radiology reporting. In this study, we proposed a keyword-based AI-assisted radiology reporting paradigm and evaluated its potential for…
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Depressive symptoms pose a serious global threat to well-being, highlighting the need for scalable mental health interventions. E-mental health interventions offer promising population-level solutions, yet few are grounded in theory or tested on large…
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