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Dermatology Practical & Conceptual
By Fatma Karataş Albayrak, Melissa Gedik Melissa Gedik, Burak Onur Zerde Burak Onur Zerde and 4 others.
Artificial intelligence-supported systems are increasingly utilized in dermatology as adjunctive diagnostic tools.
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To evaluate the diagnostic performance of ChatGPT and Google Lens in skin lesions requiring biopsy, comparing the concordance of dermatologists' clinical diagnoses and AI-generated diagnoses with histopathological findings.
In this prospective observational study, 152 adult patients with biopsy indications were included. Clinical diagnoses were established by dermatologists. Standardized lesion images were uploaded to ChatGPT (GPT-4 model, accompanied by standardized anamnesis and localization) and Google Lens (single clinical image). Diagnoses were compared with histopathological results to calculate accuracy rates using SPSS 26.0.
Mean patient age was 52.37 ± 16.63 years (55.3% male). Dermatologists achieved significantly higher diagnostic accuracy than ChatGPT (86.2% vs. 56.6%; absolute difference: 29.6 percentage points; 95% CI: 20.7–37.9) and Google Lens (86.2% vs. 31.6%; absolute difference: 54.6 percentage points; 95% CI: 45.4–62.2). By disease subtype, dermatologists outperformed both AI systems in inflammatory and drug-induced dermatoses, whereas for autoimmune bullous diseases, dermatologists and ChatGPT showed significantly higher accuracy than Google Lens.
Under the defined protocol conditions, clinical evaluation demonstrated higher diagnostic concordance than ChatGPT and Google Lens.
Published in Dermatology Practical & Conceptual. The abstract is shown as published and remains the work of its authors; read the full article at the source.
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