Background: Hospital readmissions are a key indicator of care quality, and the emergency department (ED) often serves as an entry point in the readmission cycle. To reduce avoidable acute care use, many health systems…
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Continuous prediction of glucose levels and hypoglycemia events is critical for managing type 1 diabetes mellitus (T1DM) under intensive insulin therapy. Existing models focus on a single task, limiting their practicality and adaptability in…
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Dr Indrajeet Das, consultant radiologist at University Hospitals of Leicester NHS Trust (Credit: UHL)
University Hospitals of Leicester NHS Trust is evaluating the safety and effectiveness of using AI software across different patient groups.
Specialist…
Nearly every physician I meet wants to talk about AI scribe solutions, and whether I think they will truly help put the joy back in medicine.
The first thing I think about when confronted…
Background: Surgical procedures and their potential complications place substantial strain on patients, clinicians, and health care systems. These strains are driven by the anticipated morbidity and mortality, so that there is resource-intensive postoperative inpatient…
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These technologies introduce new considerations regarding safety and effectiveness across the total product life cycle.The Food and Drug Administration is requesting public comment to get feedback on current, practical approaches to measuring and evaluating…
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To address the diversity of skin conditions and the low prevalence of skin cancers, we curated a large hospital dataset (National Information Society Agency, Seoul, Korea [NIA] dataset; 70 diseases, 152,443 images) and collected…
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Background: Obesity and related disorders are rising globally, especially in China, where they are linked to chronic diseases like diabetes and cardiovascular issues. As intermittent fasting gains popularity for weight management, the use of…
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Recent advances in artificial intelligence, particularly large language models (LLMs), show promise for mental health applications, including the automated detection of depressive symptoms from natural language. We fine-tuned a German BERT-based LLM to predict…
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While large language models (LLMs) hold promise for transforming clinical healthcare, current comparisons and benchmark evaluations of large language models in medicine often fail to capture real-world efficacy. Specifically, we highlight how key discrepancies…
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