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Accepted for/Published in: JMIR Dermatology

Date Submitted: Oct 10, 2024
Date Accepted: Jan 16, 2025

The final, peer-reviewed published version of this preprint can be found here:

Assessing the Diagnostic Accuracy of ChatGPT-4 in Identifying Diverse Skin Lesions Against Squamous and Basal Cell Carcinoma

Chetla N, Chen M, Chang J, Smith A, Gardner A, Bryer B

Assessing the Diagnostic Accuracy of ChatGPT-4 in Identifying Diverse Skin Lesions Against Squamous and Basal Cell Carcinoma

JMIR Dermatol 2025;8:e67299

DOI: 10.2196/67299

PMID: 40116774

PMCID: 11951809

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Assessing the Diagnostic Accuracy of ChatGPT-4 in Identifying Diverse Skin Lesions against Squamous and Basal Cell Carcinoma

  • Nitin Chetla; 
  • Matthew Chen; 
  • Joseph Chang; 
  • Aaron Smith; 
  • Alana Gardner; 
  • Bridget Bryer

ABSTRACT

Abstract: Our study evaluates the diagnostic accuracy of ChatGPT-4o in classifying various skin lesions, highlighting its limitations in distinguishing squamous cell carcinoma from basal cell carcinoma using dermatoscopic images.


 Citation

Please cite as:

Chetla N, Chen M, Chang J, Smith A, Gardner A, Bryer B

Assessing the Diagnostic Accuracy of ChatGPT-4 in Identifying Diverse Skin Lesions Against Squamous and Basal Cell Carcinoma

JMIR Dermatol 2025;8:e67299

DOI: 10.2196/67299

PMID: 40116774

PMCID: 11951809

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