activity
20242026
collaborators

5 papers

cs.AI2026

Scaling Clinical Judgment to Evaluate Medical AI

Thomas A. Buckley, Zahir Kanjee, Peter G. Brodeur +14

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,…

cs.CV2026

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…

cs.CV2025

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…

cs.AI2025

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…

cs.AI2024

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…