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

Research Letter (200) Skin Cancer and Melanoma Prevention (171) Digital Photography and Imaging in Dermatology (66) Chatbots and Conversational Agents (1245) Generative Language Models Including ChatGPT (1646)

Published on in Vol 8 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67551, first published .
Dermatologist examines mole with magnifying glass, skin cancer check

Evaluating the Diagnostic Accuracy of ChatGPT-4 Omni and ChatGPT-4 Turbo in Identifying Melanoma: Comparative Study

Evaluating the Diagnostic Accuracy of ChatGPT-4 Omni and ChatGPT-4 Turbo in Identifying Melanoma: Comparative Study

Authors of this article:

Samantha S. Sattler1 Author Orcid Image ;   Nitin Chetla2 Author Orcid Image ;   Matthew Chen3 Author Orcid Image ;   Tamer Rajai Hage4 Author Orcid Image ;   Joseph Chang5 Author Orcid Image ;   William Young Guo1 Author Orcid Image ;   Jeremy Hugh1 Author Orcid Image
Article Authors Cited by (14) Tweetations Metrics

Journals

  1. Keplinger L, Hu G. Limitations of ChatGPT in Dermatologic Image Analysis: Toward Broader and Deeper Evaluation. Journal of Investigative Dermatology 2025;145(12):3187 View
  2. Liu Y, Zhang Y. ChatGPT as a clinical support tool: A comprehensive review of applications, assessment, and implementation challenges. Physiotherapy Practice and Research 2026;47(1):160 View
  3. Ferrari S, Negro S, Celotto F, Bao Q, Madeo G, Pulvirenti A, Spolverato G. Artificial intelligence for post-polypectomy surveillance: a scoping review of emerging tools in colorectal cancer prevention. Artificial Intelligence Surgery 2025;5(4):490 View
  4. Wang Q, Amugo I, Rajakaruna H, Irudayam M, Xie H, Shanker A, Adunyah S. Evaluating GPT-5 for Melanoma Detection Using Dermoscopic Images. Diagnostics 2025;15(23):3052 View
  5. Ünal E, Yücel M, Gedikli S, Akay B. ChatGPT-4o as a diagnostic tool for skin cancer: Diagnostic accuracy in melanoma and non-melanoma detection. Cutaneous and Ocular Toxicology 2026;45(1):43 View
  6. Rahman S, Hosain M, Fahad N, Morol M, Hossen M. Agentic artificial intelligence is the future of cancer detection and diagnosis. Array 2026;29:100676 View
  7. Cassar P, Galea F, Ferry P. Evaluating the Clinical Decision-Making Accuracy of Artificial Intelligence in Common Geriatric Syndromes Using Evidence-Based Guidelines. Cureus 2026 View
  8. Ünal E, Duman Günsay D, Yücel M. Evaluating ChatGPT-5 for the Diagnosis of Benign Skin Lesions: Insights from Macroscopic and Dermoscopic Imaging. Archives of Current Medical Research 2026;7(1):171 View
  9. Amugo I, Frederickson K, Rajakaruna H, Xie H, Gangula P, Shanker A, Wang Q. Evaluation of GPT-5 in Periodontitis Staging and Grading: Retrospective Observational Study. JMIR Formative Research 2026;10:e88407 View
  10. Ju E, Sinharoy A, Edmonds N, Flowers R. Diagnostic Accuracy of Three Large Language Models on Clinical Images Varies by Skin Tone: Findings From the Stanford Diverse Dermatology Images Dataset. International Journal of Dermatology 2026;65(8):1783 View
  11. Kirchberger M. A 2-Tiered Rescue Protocol to Mitigate Difficulty-Based Failures of ChatGPT (GPT-5) and Gemini on the German M2 Medical Examination: Evaluation Study. JMIR Formative Research 2026;10:e86999 View
  12. Khan H, Mirza I, Aftab O, Shah Y, Al‐Khazraji A. Evaluating ChatGPT‐5 for Detection of Barrett's Esophagus and Grading of Esophagitis: A Multiclass Endoscopic Image Analysis. JGH Open 2026;10(7) View
  13. Caf N, Özkoca D, Üstünbaş Uzunçakmak T, Kutlubay Z. How appropriate are ChatGPT-5’s answers to acne questions?. Medicine 2026;105(38):e50664 View
  14. Karataş Albayrak F, Melissa Gedik M, Burak Onur Zerde B, Cansu Altınöz Güney C, Esra Uçaryılmaz Özhamam E, Fadime Kılınç F, Akın Aktaş A. Comparative Assessment of Diagnostic Concordance Among Clinical Examination, ChatGPT-4, Google Lens, and Histopathology in Dermatological Lesions. Dermatology Practical & Conceptual 2026;16(S1):7708 View