From the 1 of 4 linked papers with an AI index.
4 papers
Evaluating Large Language Models on Misconceptions in Multi-Turn Medical Conversations
Monica Munnangi, Saiph Savage
The paper introduces ThReadMed-QA, a multi‑turn medical dialogue dataset, and evaluates how well large language models can detect and correct patient misconceptions across conversa…
ThReadMed-QA: A Multi-Turn Medical Dialogue Benchmark from Real Patient Questions
Monica Munnangi, Saiph Savage
Medical question-answering benchmarks predominantly evaluate single-turn exchanges, failing to capture the iterative, clarification-seeking nature of real patient consultations. We…
FactEHR: A Dataset for Evaluating Factuality in Clinical Notes Using LLMs
Monica Munnangi, Akshay Swaminathan, Jason Alan Fries +8
Verifying and attributing factual claims is essential for the safe and effective use of large language models (LLMs) in healthcare. A core component of factuality evaluation is fac…
A Brief History of Named Entity Recognition
Monica Munnangi
A large amount of information in today's world is now stored in knowledge bases. Named Entity Recognition (NER) is a process of extracting, disambiguation, and linking an entity fr…