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Khabre desk
Recent reporting, analysis and explainers from the clinical-ai desk.
health
A medRxiv preprint tested eight general-purpose large language models on 100 neurology board-style questions. Confidence estimates were often too high, while agreement across repeated answers best distinguished correct from incorrect responses.
health
A medRxiv preprint introduces KampoBench, a physician-revised benchmark testing 10 large language models on 74 Japanese Kampo consultation scenarios. The results point to a gap between naming relevant information and applying it to a specific case.
health
A medRxiv preprint describes MINT, a foundation model trained and validated on 766,733 pediatric emergency visits. The authors report advantages over task-specific models in 21 of 25 comparisons and stronger performance than physicians on one respiratory-support forecasting task.
health
Researchers report a framework that combines language-model extraction from clinical notes with structured EHR data to build computable patient trajectories. In a GLP-1 receptor agonist analysis, it tracked weight, HbA1c and note-derived outcomes over time.