568 citations · 1.3k across the 79 of their papers we have counts for
13 papers · 1 filter
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…
MedDec: A Dataset for Extracting Medical Decisions from Discharge Summaries
Mohamed Elgaar, Jiali Cheng, Nidhi Vakil +2
Medical decisions directly impact individuals' health and well-being. Extracting decision spans from clinical notes plays a crucial role in understanding medical decision-making pr…
Evaluating the Impact of Pulse Oximetry Bias in Machine Learning under Counterfactual Thinking
Inês Martins, João Matos, Tiago Gonçalves +3
Algorithmic bias in healthcare mirrors existing data biases. However, the factors driving unfairness are not always known. Medical devices capture significant amounts of data but a…
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias
Shan Chen, Jack Gallifant, Mingye Gao +12
Large language models (LLMs) are increasingly essential in processing natural languages, yet their application is frequently compromised by biases and inaccuracies originating in t…
Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks
Jack Gallifant, Shan Chen, Pedro Moreira +7
Medical knowledge is context-dependent and requires consistent reasoning across various natural language expressions of semantically equivalent phrases. This is particularly crucia…