Two recent studies in surgical AI video analysis show divergent outcomes based on user expertise and AI explainability. While both demonstrate improved accuracy with AI-assistance, differences in trust and transparency critically shaped impact. This…
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This study introduces a machine learning framework to predict effective antiviral combinations for influenza A. It identifies Pimodivir with Epinephrine or L-Adrenaline as synergistic agents, confirmed by experiments demonstrating increased binding affinity and viral…
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Careful selection of skin lesions that require expert evaluation is important for early skin cancer detection. Yet challenges include lack of cost-effective asymptomatic screening, geographical inequality in access to specialty dermatology, and long wait…
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Chronic pain (CP) is a debilitating condition that extends beyond persistent pain, influenced by physiological and psychological factors. However, clinical trials often evaluate outcomes solely on self-reported pain amplitude. To address this, we aimed…
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Atrial fibrillation (AF) is the most common arrhythmia worldwide and is associated with significant morbidity and mortality. FibriCheck is a medical analysis platform that uses an end-to-end algorithm to detect AF based on photoplethysmography…
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Primary eye care providers refer glaucoma patients using their clinical experience and context. Specialized Artificial Intelligence (AI) excels in referrals trained on clinical data but relies on assumptions that may not hold in practice….
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Delirium affects 50% of hospitalized older adults and 80% of ICU patients, yet detection rates are as low as 20–30% with traditional methods. Natural language processing (NLP) offers potential for automated detection from clinical…
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Accurate characterization of atherosclerotic plaques in intravascular ultrasound (IVUS) imaging is essential for evaluating coronary artery disease and guiding clinical interventions. Traditional methods rely on handcrafted features and rule-based algorithms, which lack adaptability to…
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Patient face images provide a convenient mean for evaluating eye diseases, while also raising privacy concerns. Here, we introduce ROFI, a deep learning-based privacy protection framework for ophthalmology. Using weakly supervised learning and neural…
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Dry eye disease (DED) is exacerbated by prolonged screen use, partly due to reduced blink frequency and a higher percentage of incomplete blinks (IB). In this prospective, randomized study, we assessed whether a smartphone‑based…
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