Digital screening may divert lower-risk persons to lower-cost online screening, or offer higher-risk non-responders a more acceptable alternative. Population-based uptake estimates are lacking. We conducted four studies within four weeks by inviting 1700 Londoners…
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Existing reviews have identified factors influencing Clinical Decision Support (CDS) adoption by clinicians in practice but overlook the dynamic and evolving nature of technology and users’ needs over time. This review aimed to identify…
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Digital therapeutics (DTx) provide innovative treatment options. In this study, we identified and compared approved DTx in China, the US, Germany, and Belgium. In total, 507 DTx applications were identified (US, 192; China, 235;…
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The complexities inherent in EHR data create discrepancies between real-world evidence and RCTs, posing substantial challenges in determining whether a treatment is likely to have a beneficial impact compared to the standard of care…
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Preoperative detection of pT3a invasion in non-metastatic renal cell carcinoma (RCC) remains challenging with CT. This study developed and validated radiomic models using preoperative CT to identify pT3a invasions. Six models were trained and…
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A uniform and harmonised taxonomy of Digital Medical Devices (DMDs) and their evidence-based evaluation are essential to ensure their integration into healthcare systems across the European Union (EU). As part of the Taskforce for…
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The assessment of corneal fluorescein staining is essential, yet current AI models for Corneal Staining Score (CSS) assessments inadequately identify punctate lesions due to annotation challenges and noise, risk misrepresenting treatment responses through “plateau”…
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Accurate prediction of prognosis and postoperative radiotherapy response is critical for personalized treatment in head and neck squamous cell carcinoma (HNSCC). We developed a multimodal deep learning model (MDLM) integrating computed tomography, whole-slide images,…
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Extracting structured data from free-text medical records at scale is laborious, and traditional approaches struggle in complex clinical domains. We present a novel, end-to-end pipeline leveraging large language models (LLMs) for highly accurate information…
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This perspective provides a critical framework for evaluating the use of Generative AI (GenAI) in healthcare, informed by two roundtable events and a series of semi-structured expert interviews. By outlining key principles and risks—including…
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