3 citations · 4 across the 4 of their papers we have counts for
4 papers · 1 filter
Clinician use of language models diverges from how the models are evaluated
Krithik Vishwanath, Haitong Lin, Anton Alyakin +19
Large language model (LLM) assistants are being deployed to clinicians across health systems, and judgments about their readiness rest largely on benchmark scores, most of them der…
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…