3 citations · 9 across the 12 of their papers we have counts for
3 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…
Large language models are vulnerable to incidental information in clinical documentation and reasoning
Krithik Vishwanath, Brandon Ye, Anton Alyakin +4
Large language models (LLMs) are increasingly relied upon to support ambient documentation and clinical reasoning. Here we examine the impact of a failure mode shared between these…
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…