most citedA Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models

99 citations · 100 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2026

Towards Expert-level Medical AI for Real-time Video Consultations

Mahvish Nagda, Jihyeon Lee, Matthew Thompson +37

Audio-visual interaction is the standard for patient-physician consultations, enabling natural communication and effective assessment of illness through non-verbal cues. While text…

cs.AI2026

ResidencyRL: Reinforcement Learning in Simulated Clinical Environments

Valentin Liévin, Samuel Schmidgall, Tim Strother +32

In medical education, physicians convert academic knowledge into clinical expertise through residency: years of training across thousands of encounters, with diverse sources of fee…

cs.HC2026

Patients With Personality: Realistic Patient Simulation through Controlled Diversity and Selective Disclosure

Moritz Schlager, Friederike Jungmann, Samuel Schmidgall +12

Simulating realistic patient interactions is a key requirement to testing clinical applications of LLMs at scale without time-consuming and expensive user studies. However, existin…

cs.HC2026★ 1 cited

A prospective clinical feasibility study of a conversational diagnostic AI in an ambulatory primary care clinic

Peter Brodeur, Jacob M. Koshy, Anil Palepu +45

Large language model (LLM)-based AI systems have shown promise for patient-facing diagnostic and management conversations in simulated settings. Translating these systems into clin…

cs.CY2024★ 99 cited

A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models

Stephen R. Pfohl, Heather Cole-Lewis, Rory Sayres +27

Large language models (LLMs) hold promise to serve complex health information needs but also have the potential to introduce harm and exacerbate health disparities. Reliably evalua…

eess.IV2024

Closing the AI generalization gap by adjusting for dermatology condition distribution differences across clinical settings

Rajeev V. Rikhye, Aaron Loh, Grace Eunhae Hong +23

Recently, there has been great progress in the ability of artificial intelligence (AI) algorithms to classify dermatological conditions from clinical photographs. However, little i…