Performance of ChatGPT-4o, Claude 3 Opus, and DeepSeek-R1 in BI-RADS Category 4 Classification and Malignancy Prediction From Mammography Reports: Retrospective Diagnostic Study.

ABSTRACT:

Background

Mammography is a key imaging modality for breast cancer screening and diagnosis, with the Breast Imaging Reporting and Data System (BI-RADS) providing standardized risk stratification. However, BI-RADS category 4 lesions pose a diagnostic challenge due to their wide malignancy probability range and substantial overlap between benign and malignant findings. Moreover, current interpretations rely heavily on radiologists' expertise, leading to variability and potential diagnostic errors. Recent advances in large language models (LLMs), such as ChatGPT-4o, Claude 3 Opus, and DeepSeek-R1, offer new possibilities for automated medical report interpretation.

Objective

This study aims to explore the feasibility of LLMs in evaluating the benign or malignant subcategories o

SUBMITTER: Dai X 

PROVIDER: S-EPMC12784141 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature