This paper is in the following e-collection/theme issue:

AI Language Models in Health Care (61) Advanced Data Analytics in eHealth (142) Machine Learning (1501) Pathology and Laboratory Medicine (13) AI applications in genomics and pathology informatics, including ‘Generative AI’ (9) Immunoinformatics and Pathology informatics (13) Applications of AI (104)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65033, first published .
Exploring the Potential of Claude 3 Opus in Renal Pathological Diagnosis: Performance Evaluation

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

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

Authors of this article:

Xingyuan Li1 Author Orcid Image ;   Ke Liu1 Author Orcid Image ;   Yanlin Lang1 Author Orcid Image ;   Zhonglin Chai2 Author Orcid Image ;   Fang Liu1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Xingyuan Li   1 * , MS ;   Ke Liu   1 * , MS ;   Yanlin Lang   1 * , MS ;   Zhonglin Chai   2 , Prof Dr ;   Fang Liu   1 , Prof Dr Med

1 Department of Nephrology, West China Hospital, Sichuan University, Chengdu, China

2 Department of Diabetes, Central Clinical School, Monash University, Melbourne, Australia

*these authors contributed equally

Corresponding Author:

  • Fang Liu, Prof Dr Med
  • Department of Nephrology
  • West China Hospital
  • Sichuan University
  • 37 Guoxue Alley
  • Wuhou District
  • Chengdu, 610041
  • China
  • Phone: 86 13890790651
  • Email: liufangfh@163.com