1 citations · 2 across the 6 of their papers we have counts for
13 papers
CLExEval: A Human-in-the-Loop Framework for Qualitative Evaluation of LLM Clinical Reasoning
Ajmal M., Abin Roy, Afthab Salam Kanniyan +4
Large Language Models (LLMs) achieve strong results on many medical benchmarks, but their clinical reasoning remains difficult to evaluate reliably. A central risk is an evaluation…
A global log for medical AI
Ayush Noori, Aaron E. Boussina, Hai Ho Bich +48
Modern computer systems rely on syslog, a universal protocol that records critical events across heterogeneous infrastructure. Medicine's rapidly growing AI stack has no equivalent…
Teaching large language models to reason like expert diagnosticians
Thomas A. Buckley, Riccardo Conci, Peter G. Brodeur +23
Differential diagnosis is an iterative process that integrates patient information with broader medical knowledge. Clinical case series such as the NEJM Clinicopathologic Conferenc…
RadGame: An AI-Powered Platform for Radiology Education
Mohammed Baharoon, Siavash Raissi, John S. Jun +29
We introduce RadGame, an AI-powered gamified platform for radiology education that targets two core skills: localizing findings and generating reports. Traditional radiology traini…
ER-Reason: A Benchmark Dataset for LLM Clinical Reasoning in the Emergency Room
Nikita Mehandru, Niloufar Golchini, Namrata Garg +9
Existing benchmarks for evaluating the clinical reasoning capabilities of large language models (LLMs) often lack a clear definition of "clinical reasoning" as a construct, fail to…
Towards Conversational Medical AI with Eyes, Ears and a Voice
Meet Shah, Jason Gusdorf, Anil Palepu +50
The practice of medicine relies not only upon skillful dialogue but also on the nuanced exchange and interpretation of rich auditory and visual cues between doctors and patients. B…