{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T23:03:28Z","timestamp":1789513408939,"version":"build-2803163510"},"reference-count":19,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T00:00:00Z","timestamp":1780358400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T00:00:00Z","timestamp":1789516800000},"content-version":"vor","delay-in-days":106,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Digit. Med."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Artificial intelligence (AI) shows promise in analyzing patterns of nail disease. This prospective, comparative study compared the diagnostic performance of dermatologists with that of large language models (LLMs). We evaluated the diagnostic accuracy of dermatologists and four freely available multimodal LLMs (GPT-4o, Grok 3, Claude Sonnet 4, and Gemini 2.5 Flash) using clinical images of nail diseases. Seventeen dermatologists correctly diagnosed the primary suspected diagnosis (SD) in 70.6% (95% CI: 65.5\u201375.2) of cases, and in 80.3% (95% CI: 75.7\u201384.2) of cases when considering both the SD and the differential diagnosis (SD\u2009+\u2009DD). Accuracy increased across dermatologist groups, ranging from residents (68.3% for SD\u2009+\u2009DD) to nail disease experts (96.0%). In comparison, AI models were correct in 25.0% (95% CI: 16.8\u201335.5) and 35.0% (95% CI: 25.5\u201345.9) of cases, respectively (\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.001). The AI algorithms correctly classified 13.9% of tumors and 52.3% of non-tumors (SD\u2009+\u2009DD,\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.001). Current freely available general-purpose AI models demonstrated limited reliability for standalone nail disease diagnosis in this exploratory setting and should not be used without clinical supervision. While these systems may assist in suggesting differential diagnoses, their performance remains variable and requires further validation in larger, clinically representative datasets.\n                  <\/jats:p>","DOI":"10.1038\/s41746-026-02850-9","type":"journal-article","created":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T07:46:15Z","timestamp":1780386375000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Human expertise or artificial intelligence? A prospective study on nail disorder diagnosis"],"prefix":"10.1038","volume":"9","author":[{"given":"Flurin L.","family":"Brand","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Mokhtari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simone","family":"Cazzaniga","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christoph","family":"Brand","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cindy","family":"Franklin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan","family":"Furrer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chander","family":"Grover","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eckart","family":"Haneke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristine","family":"Heidemeyer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matilde","family":"Iorizzo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandra","family":"Junge","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christine A.","family":"Langhorst","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shari R.","family":"Lipner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luigi","family":"Naldi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Talisa Luana","family":"Ragonsesi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sanjive","family":"Rey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bertrand","family":"Richert","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Basil","family":"Signer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charlotte","family":"Vogel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikhil","family":"Yawalkar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sven","family":"Z\u00fcrcher","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dominik","family":"Obrist","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S. Morteza","family":"Seyed Jafari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,2]]},"reference":[{"key":"2850_CR1","doi-asserted-by":"publisher","first-page":"40","DOI":"10.4103\/idoj.idoj_460_24","volume":"16","author":"V Gaurav","year":"2025","unstructured":"Gaurav, V., Grover, C., Tyagi, M. & Saurabh, S. Artificial intelligence in diagnosis and management of nail disorders: a narrative review. Indian Dermatol. Online J. 16, 40\u201349 (2025).","journal-title":"Indian Dermatol. Online J."},{"key":"2850_CR2","doi-asserted-by":"crossref","unstructured":"Khamaysi, Z., Awwad, M., Jiryis, B., Bathish, N. & Shapiro, J. The role of ChatGPT in dermatology diagnostics. Diagnostics 15, 1529 (2025).","DOI":"10.3390\/diagnostics15121529"},{"key":"2850_CR3","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-53303-w","volume":"14","author":"KF Hubert","year":"2024","unstructured":"Hubert, K. F., Awa, K. N. & Zabelina, D. L. The current state of artificial intelligence generative language models is more creative than humans on divergent thinking tasks. Sci. Rep. 14, 3440 (2024).","journal-title":"Sci. Rep."},{"key":"2850_CR4","doi-asserted-by":"publisher","DOI":"10.2196\/48568","volume":"25","author":"J Liu","year":"2023","unstructured":"Liu, J., Wang, C. & Liu, S. Utility of ChatGPT in clinical practice. J. Med. Internet Res. 25, e48568 (2023).","journal-title":"J. Med. Internet Res."},{"key":"2850_CR5","first-page":"574","volume":"3","author":"R Regin","year":"2022","unstructured":"Regin, R., Reddy, G. G., Kumar Ch, S. & Cvn, J. Nail disease detection and classification using deep learning. Cent. Asian J. Med. Nat. Sci. 3, 574\u2013594 (2022).","journal-title":"Cent. Asian J. Med. Nat. Sci."},{"key":"2850_CR6","doi-asserted-by":"publisher","first-page":"e1533","DOI":"10.7717\/peerj-cs.1533","volume":"9","author":"DY Co\u015far So\u011fukkuyu","year":"2023","unstructured":"Co\u015far So\u011fukkuyu, D. Y. & Ata, O. Classification of melanonychia, Beau\u2019s lines, and nail clubbing based on nail images and transfer learning techniques. PeerJ Comput. Sci. 9, e1533 (2023).","journal-title":"PeerJ Comput. Sci."},{"key":"2850_CR7","doi-asserted-by":"crossref","unstructured":"Hadiyoso, S. & Aulia, S. Classification of Koilonychia, Beaus Lines, and Leukonychia based on nail image using transfer learning VGG-16. J. Rekayasa Elektr. 18, 109\u2013114 (2022).","DOI":"10.17529\/jre.v18i2.25694"},{"key":"2850_CR8","doi-asserted-by":"publisher","first-page":"e0191493","DOI":"10.1371\/journal.pone.0191493","volume":"13","author":"SS Han","year":"2018","unstructured":"Han, S. S. et al. Deep neural networks show an equivalent and often superior performance to dermatologists in onychomycosis diagnosis: automatic construction of onychomycosis datasets by region-based convolutional deep neural network. PLoS ONE 13, e0191493 (2018).","journal-title":"PLoS ONE"},{"key":"2850_CR9","first-page":"78","volume":"28","author":"ME Boon","year":"2006","unstructured":"Boon, M. E., Berger, T. H., Middag-Broekman, A. J. & Kok, L. P. Optimized quality of histologic images allows the use of neural network scanning in diagnosis of fungal infection of abnormal nails. Anal. Quant. Cytol. Histol. 28, 78\u201386 (2006).","journal-title":"Anal. Quant. Cytol. Histol."},{"key":"2850_CR10","doi-asserted-by":"crossref","unstructured":"Jansen, P. et al. Deep learning assisted diagnosis of onychomycosis on whole-slide images. J. Fungi 8, 912 (2022).","DOI":"10.3390\/jof8090912"},{"key":"2850_CR11","doi-asserted-by":"publisher","first-page":"466","DOI":"10.1111\/myc.13427","volume":"65","author":"X Zhu","year":"2022","unstructured":"Zhu, X. et al. Deep learning-based diagnosis models for onychomycosis in dermoscopy. Mycoses 65, 466\u2013472 (2022).","journal-title":"Mycoses"},{"key":"2850_CR12","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-023-32440-8","volume":"13","author":"L Folle","year":"2023","unstructured":"Folle, L. et al. DeepNAPSI multi-reader nail psoriasis prediction using deep learning. Sci. Rep. 13, 5329 (2023).","journal-title":"Sci. Rep."},{"key":"2850_CR13","doi-asserted-by":"publisher","first-page":"1057","DOI":"10.1016\/j.jaad.2023.12.062","volume":"90","author":"N Shifai","year":"2024","unstructured":"Shifai, N., van Doorn, R., Malvehy, J. & Sangers, T. E. Can ChatGPT vision diagnose melanoma? An exploratory diagnostic accuracy study. J. Am. Acad. Dermatol. 90, 1057\u20131059 (2024).","journal-title":"J. Am. Acad. Dermatol."},{"key":"2850_CR14","doi-asserted-by":"publisher","first-page":"900","DOI":"10.1038\/s41591-020-0842-3","volume":"26","author":"Y Liu","year":"2020","unstructured":"Liu, Y. et al. A deep learning system for differential diagnosis of skin diseases. Nat. Med. 26, 900\u2013908 (2020).","journal-title":"Nat. Med."},{"key":"2850_CR15","doi-asserted-by":"publisher","DOI":"10.1126\/sciadv.abq6147","volume":"8","author":"R Daneshjou","year":"2022","unstructured":"Daneshjou, R. et al. Disparities in dermatology AI performance on a diverse, curated clinical image set. Sci. Adv. 8, eabq6147 (2022).","journal-title":"Sci. Adv."},{"key":"2850_CR16","doi-asserted-by":"publisher","first-page":"e202","DOI":"10.1111\/ajd.14484","volume":"66","author":"M Lewandowski","year":"2025","unstructured":"Lewandowski, M., Kropid\u0142owska, J., Kvinen, A. & Bara\u0144ska-Rybak, W. A systemic review of large language models and their implications in dermatology. Australas. J. Dermatol. 66, e202\u2013e208 (2025).","journal-title":"Australas. J. Dermatol."},{"key":"2850_CR17","doi-asserted-by":"publisher","first-page":"789","DOI":"10.1093\/bjd\/ljae040","volume":"190","author":"ER Gordon","year":"2024","unstructured":"Gordon, E. R. et al. Ethical considerations for artificial intelligence in dermatology: a scoping review. Br. J. Dermatol 190, 789\u2013797 (2024).","journal-title":"Br. J. Dermatol"},{"key":"2850_CR18","doi-asserted-by":"publisher","first-page":"879","DOI":"10.1016\/j.jaad.2023.02.052","volume":"90","author":"EJ Beltrami","year":"2024","unstructured":"Beltrami, E. J. & Grant-Kels, J. M. Consulting ChatGPT: ethical dilemmas in language model artificial intelligence. J. Am. Acad. Dermatol. 90, 879\u2013880 (2024).","journal-title":"J. Am. Acad. Dermatol."},{"key":"2850_CR19","unstructured":"Gwet, K. Handbook of Inter-rater Reliability: The Definitive Guide to Measuring the Extent of Agreement Among Raters (Advanced Analytics, LLC, 2012)."}],"container-title":["npj Digital Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-02850-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-02850-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-02850-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T22:29:54Z","timestamp":1789511394000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-02850-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,2]]},"references-count":19,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["2850"],"URL":"https:\/\/doi.org\/10.1038\/s41746-026-02850-9","relation":{},"ISSN":["2398-6352"],"issn-type":[{"value":"2398-6352","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,2]]},"assertion":[{"value":"24 December 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 June 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Ethics"}}],"article-number":"705"}}