26 citations · 45 across the 5 of their papers we have counts for
6 papers
Scaling Clinical Judgment to Evaluate Medical AI
Thomas A. Buckley, Zahir Kanjee, Peter G. Brodeur +15
Blinded physician evaluation has been considered by many to be the gold standard for assessing clinical reasoning in large language models (LLMs). This is difficult to scale; thus,…
How Seemingly Inconsequential Design Choices Dictate Performance of LLMs in Pathology
Kian R. Weihrauch, Thomas A. Buckley, William Lotter +1
General-purpose large language models (LLMs) are routinely used as baselines when evaluating specialized pathology models on whole-slide images (WSIs). Because WSIs exceed contempo…
Navigating Gigapixel Pathology Images with Large Multimodal Models
Thomas A. Buckley, Kian R. Weihrauch, Katherine Latham +3
Recent advances in large multimodal models have allowed for the development of interactive chat models that can converse and reason about pathology whole-slide images (WSIs). Howev…
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…
Superhuman performance of a large language model on the reasoning tasks of a physician
Peter G. Brodeur, Thomas A. Buckley, Zahir Kanjee +22
A seminal paper published by Ledley and Lusted in 1959 introduced complex clinical diagnostic reasoning cases as the gold standard for the evaluation of expert medical computing sy…
Multimodal Foundation Models Exploit Text to Make Medical Image Predictions
Thomas Buckley, James A. Diao, Pranav Rajpurkar +2
Multimodal foundation models have shown compelling but conflicting performance in medical image interpretation. However, the mechanisms by which these models integrate and prioriti…