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Previously submitted to: JMIR Dermatology (no longer under consideration since Aug 06, 2024)

Date Submitted: Jul 13, 2024
Open Peer Review Period: Aug 6, 2024 - Aug 6, 2024
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ChatGPT and The Suspicion of Skin Cancer, a Diagnostic Accuracy Study

  • William Abou Shahla; 
  • Firas Haddad; 
  • Mariana El Hawa; 
  • Dana Saade

ABSTRACT

Background:

While ChatGPT is user-friendly and widely accessible, concerns arise regarding potential delays in diagnosis and false reassurances for patients with suspected skin malignancies.

Objective:

Our study aims to assess the accuracy of AI, specifically ChatGPT, in diagnosing skin malignancies and expressing the urgency to seek medical advice.

Methods:

This diagnostic accuracy study assesses the agreement between dermatologists' final diagnoses and those provided by ChatGPT when patients describe their lesions. Thirty-five patients, suspected of skin cancer (SCC/BCC), provided demographic details and lesion descriptions. Diagnoses were recorded in ChatGPT3.5 and ChatGPT4.0 for analysis.

Results:

Out of 35 lesions suspected by the dermatologist, all were malignant, indicating 100% accuracy. ChatGPT3.5 flagged malignancy in 7 cases (20%), while ChatGPT4.0 did so in 6 cases (17.14%). Consistency was lacking, as only 7 lesions received the same diagnosis from both models. However, both ChatGPT3.5 and ChatGPT4.0 referred patients to dermatologists in all cases.

Conclusions:

Both GPT models performed comparably to each other but were significantly inferior to dermatologists. However, both did not cause delays in referral to a dermatologist. The limitations of these two models include poor accuracy, lack of concordance among each other’s, and reproducibility issues with their answers.


 Citation

Please cite as:

Abou Shahla W, Haddad F, El Hawa M, Saade D

ChatGPT and The Suspicion of Skin Cancer, a Diagnostic Accuracy Study

JMIR Preprints. 13/07/2024:64272

DOI: 10.2196/preprints.64272

URL: https://preprints.jmir.org/preprint/64272

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