Critically ill children who require inter-hospital transfers to paediatric intensive care units are sicker than other admissions and have higher mortality rates. Current transport practice primarily relies on early clinical assessments within the initial…
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Pulsed radio frequency energy (PRFE) therapy is a non-invasive, electromagnetic field-based treatment modality successfully used in clinical applications. However, conventional PRFE devices are often bulky, expensive, and require extended treatment durations, limiting patient adherence…
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Depression in older adults is often underdiagnosed and has been linked to adverse outcomes, including motor vehicle crashes. With a growing population of older drivers in the United States, innovations in screening methods are…
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Distributed learning enables collaborative machine learning model training without requiring cross-institutional data sharing, thereby addressing privacy concerns. However, local quality control variability can negatively impact model performance while systematic human visual inspection is time-consuming…
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Primary cutaneous squamous cell carcinoma (cSCC) is responsible for ~10,000 deaths annually in the United States. Stratification of risk of poor outcome at initial biopsy would significantly impact clinical decision-making during the initial post…
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Applying machine learning to clinical outcome prediction is challenging due to imbalanced datasets and sensitive tasks that contain rare yet critical outcomes and where equitable treatment across diverse patient groups is essential. Despite attempts,…
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This is part two of a two-part special CDIO profile story. To read part one, click here.Building a digital ecosystem and crafting the technology elements of a health system’s five-year strategic plan are no…
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Choosing optimal revascularization strategies for patients with obstructive coronary artery disease (CAD) remains a clinical challenge. While randomized controlled trials offer population-level insights, gaps remain regarding personalized decision-making for individual patients. We applied off-policy…
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Musculoskeletal complaints account for 30% of GP consultations, with many referred to rheumatology clinics via letters. This study developed a Machine Learning (ML) pipeline to prioritize referrals by identifying rheumatoid arthritis (RA), osteoarthritis, fibromyalgia,…
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We piloted using Large Language Models (LLMs) for organizing AMIA 2024 Informatics Summit. LLMs were prompt engineered to develop algorithms for reviewer assignments, group presentations into sessions, suggest session titles, and provide one-sentence summaries…
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