3 citations · 6 across the 13 of their papers we have counts for
5 papers · 1 filter
Surrogate modeling for interpreting black-box LLMs in medical predictions
Changho Han, Songsoo Kim, Dong Won Kim +4
Large language models (LLMs), trained on vast datasets, encode extensive real-world knowledge within their parameters, yet their black-box nature obscures the mechanisms and extent…
BRIDGE: Benchmarking Large Language Models for Understanding Real-world Clinical Practice Text
Jiageng Wu, Bowen Gu, Ren Zhou +14
Large language models (LLMs) hold great promise for medical applications and are evolving rapidly, with new models being released at an accelerated pace. However, benchmarking on l…
A Dataset and Resources for Identifying Patient Health Literacy Information from Clinical Notes
Madeline Bittner, Dina Demner-Fushman, Yasmeen Shabazz +6
Health literacy is a critical determinant of patient outcomes, yet current screening tools are not always feasible and differ considerably in the number of items, question format,…
Multi-OphthaLingua: A Multilingual Benchmark for Assessing and Debiasing LLM Ophthalmological QA in LMICs
David Restrepo, Chenwei Wu, Zhengxu Tang +14
Current ophthalmology clinical workflows are plagued by over-referrals, long waits, and complex and heterogeneous medical records. Large language models (LLMs) present a promising…
WorldMedQA-V: a multilingual, multimodal medical examination dataset for multimodal language models evaluation
João Matos, Shan Chen, Siena Placino +13
Multimodal/vision language models (VLMs) are increasingly being deployed in healthcare settings worldwide, necessitating robust benchmarks to ensure their safety, efficacy, and fai…