Exploring the Potential of Claude 3 Opus in Renal Pathological Diagnosis: Performance Evaluation
Claude 3 Opus shows potential in generating fluent renal pathology descriptions but needs improvement in accuracy and clinical value. The AI's performance varied across disease types. Addressing the limitations of single-source data and incorporating comparative analyses with other AI approaches are essential steps for future research. Further optimization and validation are needed for clinical applications.
Authors
- Xingyuan Li (ORCID: https://orcid.org/0009-0009-5897-9614)
- Yanlin Lang (ORCID: https://orcid.org/0000-0002-9701-2360)
- Fang Liu (ORCID: https://orcid.org/0000-0003-1121-3004)
- Zhonglin Chai (ORCID: https://orcid.org/0000-0001-8182-8579)
- Ke Liu (ORCID: https://orcid.org/0000-0002-2903-8462)
Institutions
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
- Monash University (AU)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2024-10-19
- DOI
- https://doi.org/10.2196/65033
- Citations
- 7
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.84