4 papers
Large Language Models Predict Functional Outcomes after Acute Ischemic Stroke
Anjali K. Kapoor, Anton Alyakin, Jin Vivian Lee +8
Accurate prediction of functional outcomes after acute ischemic stroke can inform clinical decision-making and resource allocation. Prior work on modified Rankin Scale (mRS) predic…
Generalist Foundation Models Are Not Clinical Enough for Hospital Operations
Lavender Y. Jiang, Angelica Chen, Xu Han +16
Hospitals and healthcare systems rely on operational decisions that determine patient flow, cost, and quality of care. Despite strong performance on medical knowledge and conversat…
Evaluating the performance and fragility of large language models on the self-assessment for neurological surgeons
Krithik Vishwanath, Anton Alyakin, Mrigayu Ghosh +5
The Congress of Neurological Surgeons Self-Assessment for Neurological Surgeons (CNS-SANS) questions are widely used by neurosurgical residents to prepare for written board examina…
Medical large language models are easily distracted
Krithik Vishwanath, Anton Alyakin, Daniel Alexander Alber +3
Large language models (LLMs) have the potential to transform medicine, but real-world clinical scenarios contain extraneous information that can hinder performance. The rise of ass…