To address challenges in screening for chronic kidney disease (CKD), we devised a deep learning-based CKD screening model named UWF-CKDS. It utilizes ultra-wide-field (UWF) fundus images to predict the presence of CKD. We validated…
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Environmental factors amplified by climate change contribute significantly to the global burden of disease, disproportionately impacting vulnerable populations, such as individuals with rare diseases. Researchers require innovative, dynamic data linkage methods to enable the…
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Machine learning and artificial intelligence (AI/ML) models in healthcare may exacerbate health biases. Regulatory oversight is critical in evaluating the safety and effectiveness of AI/ML devices in clinical settings. We conducted a scoping review…
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Ex vivo lung perfusion (EVLP) enables advanced assessment of human lungs for transplant suitability. We developed a convolutional neural network (CNN)-based approach to analyze the largest cohort of isolated lung radiographs to date. CNNs…
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Improving health-related quality of life (QoL) is crucial for managing Parkinson’s disease. However, QoL outcomes after deep brain stimulation (DBS) of the subthalamic nucleus (STN) vary considerably. Current approaches lack integration of demographic, patient-reported,…
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Digital medical devices (DMDs) present unique opportunities in their regulation and reimbursement. A dynamic landscape of DMD assessment frameworks is emerging within the European Union, with five clusters of prevailing approaches identified. Despite notable…
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The integration of artificial intelligence (AI) in sports medicine is opening new frontiers for athlete health and performance, aligning with the spirit of the Paris 2024 Olympic Games slogan, “Games Wide Open.”…
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In healthcare, integration of artificial intelligence (AI) holds strong promise for facilitating clinicians’ work, especially in clinical imaging. We aimed to assess the impact of AI implementation for medical imaging on efficiency in real-world…
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Identifying and preventing patients who are not likely to benefit long-term from total knee arthroplasty (TKA) would decrease healthcare expenditure significantly. We trained machine learning (ML) models (image-only, clinical-data only, and multimodal) among 5720…
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Deep phenotyping describes the use of standardised terminologies to create comprehensive phenotypic descriptions of biomedical phenomena. These characterisations facilitate secondary analysis, evidence synthesis, and practitioner awareness, thereby guiding patient care. The vast majority of…
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