ChatGPT-4o Proves Effective in Accurately Diagnosing Dermoscopic Images of Benign and Malignant Skin Conditions
Main Article Content
Keywords
Dermoscopy, Artificial Intelligence, ChatGPT, Melanoma, Squamous Cell Carcinoma, Basal Cell Carcinoma
Abstract
Introduction: The integration of artificial intelligence (AI) and AI chatbots (AIC) into medicine is progressing rapidly, particularly within dermatology, where clinical, dermoscopic, and histological pattern recognition is essential.
Methods: To assess the diagnostic capabilities of ChatGPT-4o, ten skin lesions were selected: basal cell carcinoma (BCC), melanoma, invasive squamous cell carcinoma (SCC), actinic keratosis (AK), cherry angioma (CA), solar lentigo (SL), seborrheic keratosis (SK), blue nevus (BN), dermatofibroma (DF), and lichen planus (LP). For each condition, fifteen dermoscopic images were sourced from DermNet NZ and Dermoscopedia, yielding a total of 150 images. Rank order top 5 differential diagnosis were generated for each image and sensitivity, specificity, and accuracy were computed for each.
Results: ChatGPT-4o correctly diagnosed 117 out of 150 (78%) images at the first attempt, and 144 out of 150 (96%) images within the top five differential diagnoses. Melanoma was correctly identified on initial diagnosis (15/15, 100% sensitivity, 91.1% specificity, 91.99% accuracy).
Discussion: Our research demonstrates the promising potential diagnostic capabilities of ChatGPT-4o in accurately identifying various benign and malignant skin lesions using dermoscopic images, novel findings in comparison to prior studies
References
2. Cortes J, Paravar T, Oldenburg R. Physician Opinions on Artificial Intelligence Chatbots In Dermatology: A National Online Cross-Sectional Survey of Dermatologists. J Drugs Dermatol. 2024;23(11):972-978. doi:10.36849/JDD.8239
3. Demand Sage. ChatGPT statistics: Key facts and figures. Published November 2024. Accessed November 4, 2024. Available from: https://www.demandsage.com/chatgpt-statistics/#:~:text=As%20of%20November%202024%2C%20ChatGPT,reached%20an%20all%2Dtime%20high.
4. Shifai N, van Doorn R, Malvehy J, Sangers TE. Can ChatGPT vision diagnose melanoma? An exploratory diagnostic accuracy study. J Am Acad Dermatol. 2024;90(5):1057-1059. doi:10.1016/j.jaad.2023.12.062
Article Sidebar
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Creative Commons Attribution (CC BY): lets others distribute and copy the article, to create extracts, abstracts, and other revised versions, adaptations or derivative works of or from an article (such as a translation), to include in a collective work (such as an anthology), to text or data mine the article, even for commercial purposes, as long as they credit the author(s), do not represent the author as endorsing their adaptation of the article, and do not modify the article in such a way as to damage the author's honor or reputation.
Authors retain copyright in their work and license the publisher to publish the content. The publisher is the National Society for Cutaneous Medicine, with production and publishing support provided by OJS, Open Journal Systems,see https://pkp.sfu.
Prior to January 2022, authors transferred copyright to the National Society for Cutaneous Medicine. However, all articles are freely available to anyone in the world. There are no subscription fees, page charges, or article processing charges.