Large Language Models Predict Functional Outcomes after Acute Ischemic Stroke
Anjali K. Kapoor, Anton Alyakin, Jin Vivian Lee, Eunice Yang et autres
Accurate prediction of functional outcomes after acute ischemic stroke can inform clinical decision-making and resource allocation. Prior work on modified Rankin Scale (mRS) prediction has relied primarily on structured variables (e.g., age, NIHSS) and conventional machine learning. The ability of large language …
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arXiv (Cornell University)