Predictive model performance may deteriorate when applied to data sources that were not used for training, thus, external validation is a key step in successful model deployment. As access to patient-level external data sources…
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In this study, we present MedS-Bench, a comprehensive benchmark to evaluate large language models (LLMs) in clinical contexts, MedS-Bench, spanning 11 high-level clinical tasks. We evaluate nine leading LLMs, e.g., MEDITRON, Llama 3, Mistral,…
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Noninvasive methods for intracranial pressure (ICP) monitoring have emerged, but none has successfully replaced invasive techniques. This observational study developed and tested a machine learning (ML) model to estimate ICP using waveforms from a…
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Deep-learning models have shown promise in differentiating between benign and malignant lesions. Previous studies have primarily focused on specific anatomical regions, overlooking tumors occurring throughout the body with highly heterogeneous whole-body backgrounds. Using neurofibromatosis…
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Polysomnography (PSG) is crucial for diagnosing sleep disorders, but manual scoring of PSG is time-consuming and subjective, leading to high variability. While machine-learning models have improved PSG scoring, their clinical use is hindered by…
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Artificial intelligence (AI) is increasingly permeating the fabric of medicine, but getting full benefits will likely require fundamental changes in practice. Accepting this will be challenging for many clinicians. However, it may be necessary…
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This study developed and evaluated a model for assessing pain during the surgical period using photoplethysmogram data from 242 patients. Pain levels were measured at 2 min intervals using a numerical rating scale or clinical…
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Particulate matter (PM) exposure can reduce heart rate variability (HRV), a cardiovascular health marker. This study examines PM1.0 (aerodynamic diameters <1 μm), PM2.5 (≥1 μm and <2.5 μm), and PM10 (≥2.5 μm and <10 μm) effects on HRV in…
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We propose the addition of usability validation to the extended V3 framework, now “V3+”, and describe a pragmatic approach to ensuring that sensor-based digital health technologies can be used optimally at scale by diverse…
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Differentiating between diabetic nephropathy (DN) and non-diabetic renal disease (NDRD) without a kidney biopsy remains a major challenge, often leading to missed opportunities for targeted treatments that could greatly improve NDRD outcomes. To reform…
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