Clinical trial matching is the task of identifying trials for which patients may be eligible. Typically, this task is labor-intensive and requires detailed verification of patient electronic health records (EHRs) against the stringent inclusion…
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We developed and evaluated the Digital Platform for Exercise (DPEx): a decentralized, patient-centric approach designed to enhance all aspects of clinical investigation of exercise therapy. DPEx integrated provision of a treadmill with telemedicine and…
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Periprosthetic joint infection (PJI) is a severe complication after joint replacement surgery that demands precise diagnosis for effective treatment. We enhanced PJI diagnostic accuracy through three steps: (1) developing a self-supervised PJI model with…
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We investigated the potential of the transmission line model as a digital twin of aneurysmal aorta by comparatively analyzing how a uniform lossless tube-load model were fitted to the carotid and femoral artery tonometry…
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Novel products applying artificial intelligence (AI)-based methods to digital pathology images are touted to have many uses and benefits. However, publicly available information for products can be variable, with few sources of independent evidence….
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This perspective article explores how process mining can extract clinical insights from mobile health data and complement data-driven techniques like machine learning. Despite technological advances, challenges such as selection bias and the complex dynamics…
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Accurate assessment of body composition is essential for evaluating the risk of chronic disease. 3D body shape, obtainable using smartphones, correlates strongly with body composition. We present a novel method that fits a 3D…
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Emergency admissions (EA), where a patient requires urgent in-hospital care, are a major challenge for healthcare systems. The development of risk prediction models can partly alleviate this problem by supporting primary care interventions and…
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It would be clinically valuable if the efficacy of antiarrhythmic drugs could be simulated in advance. We developed a digital twin to predict amiodarone efficacy in high-risk atrial fibrillation (AF) patients post-ablation. Virtual left…
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Large language models (LLMs) have broad medical knowledge and can reason about medical information across many domains, holding promising potential for diverse medical applications in the near future. In this study, we demonstrate a…
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