Exploring the Potential of Claude 3 Opus in Renal Pathological Diagnosis: Performance Evaluation.

ABSTRACT:

Background

Artificial intelligence (AI) has shown great promise in assisting medical diagnosis, but its application in renal pathology remains limited.

Objective

We evaluated the performance of an advanced AI language model, Claude 3 Opus (Anthropic), in generating diagnostic descriptions for renal pathological images.

Methods

We carefully curated a dataset of 100 representative renal pathological images from the Diagnostic Atlas of Renal Pathology (3rd edition). The image selection aimed to cover a wide spectrum of common renal diseases, ensuring a balanced and comprehensive dataset. Claude 3 Opus generated diagnostic descriptions for each image, which were scored by 2 pathologists on clinical relevance, accuracy, fluency, completeness, and overall value.

Results<

SUBMITTER: Li X 

PROVIDER: S-EPMC11607560 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature