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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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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Biobanks are a rich source of data for genome-wide association studies (GWAS). They store clinical data from electronic health records, with data domains such as laboratory measurements, conditions, and self-reported diagnoses. Traditionally, biobank GWAS…
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Digital technologies improve health outcomes, access to education and health care. However, their application in the context of climate change is limited. This scoping review aimed to identify the use of digital technologies for…
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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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The integration of physics-based digital twins with data-driven artificial intelligence—termed “Big AI”—can advance truly personalised medicine. While digital twins offer individual ‘healthcasts,’ accuracy and interpretability, and AI delivers speed and flexibility, each has limitations….
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In (immune)oncology, virtual twins (VTs) offer patient-individual decision support. Nevertheless, current VTs do not incorporate the unique properties of engineered adoptive cellular immunotherapies (eACIs). Here, we outline the minimal design specifications for VTs for…
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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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