{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T00:08:31Z","timestamp":1790726911737,"version":"4.1.0"},"reference-count":8,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T00:00:00Z","timestamp":1785715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,9,30]]},"abstract":"<jats:p>The recent systematic review and meta-analysis by Nirula et al. reports pooled sensitivity and specificity of 89% and 82%, respectively, for artificial intelligence (AI)-based differentiation between benign and malignant skin lesions. This highlights the diagnostic potential of these tools. However, diagnostic accuracy alone does not establish clinical utility; a tool that performs well in retrospective validation may not meaningfully alter referral patterns, reduce waiting times or improve healthcare efficiency in practice. As we move closer to the implementation of AI technologies in dermatology services, future studies should evaluate implementation outcomes \u2013 including referral avoidance, biopsy rates and healthcare utilization \u2013 alongside traditional accuracy metrics.<\/jats:p>","DOI":"10.1093\/skinhd\/vzag129","type":"journal-article","created":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T11:20:17Z","timestamp":1784546417000},"page":"843-844","source":"Crossref","is-referenced-by-count":0,"title":["Beyond diagnostic accuracy: evaluating the clinical utility of artificial intelligence for suspicious lesion triage"],"prefix":"10.1093","volume":"6","author":[{"given":"Nethmi","family":"Chandrasekara","sequence":"first","affiliation":[{"name":"Postgraduate Department, Manchester Royal Infirmary, Manchester University NHS Foundation Trust , Manchester ,","place":["UK"]},{"name":"Musculoskeletal and Dermatological Sciences, School of Biological Sciences, University of Manchester , Manchester ,","place":["UK"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,8,3]]},"reference":[{"key":"2026092919521517400_vzag129-B1","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1093\/skinhd\/vzag021","article-title":"How good are artificial intelligence tools at identifying benign skin lesions?","volume":"6","author":"Nirula","year":"2026","journal-title":"Skin Health Dis"},{"key":"2026092919521517400_vzag129-B2","author":"British Association of Dermatologists"},{"key":"2026092919521517400_vzag129-B3","author":"National Institute for Health and Care Excellence (NICE)"},{"key":"2026092919521517400_vzag129-B4","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1038\/s41746-018-0048-y","article-title":"With an eye to AI and autonomous diagnosis","volume":"1","author":"Keane","year":"2018","journal-title":"NPJ Digit Med"},{"key":"2026092919521517400_vzag129-B5","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1001\/jamadermatol.2026.0217","article-title":"Prospective evidence on artificial intelligence\u2212assisted melanoma diagnostics: a systematic review and meta-analysis","volume":"162","author":"Laiouar-Pedari","year":"2026","journal-title":"JAMA Dermatol"},{"key":"2026092919521517400_vzag129-B6","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1016\/j.jid.2023.10.004","article-title":"Artificial intelligence in skin cancer diagnosis: a reality check","volume":"144","author":"Brancaccio","year":"2024","journal-title":"J Invest Dermatol"},{"key":"2026092919521517400_vzag129-B7","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1001\/jamadermatol.2026.1492","article-title":"Limits of artificial intelligence models for skin cancer diagnosis in realistic settings","volume":"162","author":"Anriot","year":"2026","journal-title":"JAMA Dermatol"},{"key":"2026092919521517400_vzag129-B8","doi-asserted-by":"crossref","first-page":"e070904","DOI":"10.1136\/bmj-2022-070904","article-title":"Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI","volume":"377","author":"Vasey","year":"2022","journal-title":"BMJ"}],"container-title":["Skin Health and Disease"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/skinhd\/article-pdf\/6\/5\/843\/70470510\/vzag129.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/skinhd\/article-pdf\/6\/5\/843\/70470510\/vzag129.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T23:52:25Z","timestamp":1790725945000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/skinhd\/article\/6\/5\/843\/8750232"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,3]]},"references-count":8,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2026,8,3]]},"published-print":{"date-parts":[[2026,9,30]]}},"URL":"https:\/\/doi.org\/10.1093\/skinhd\/vzag129","relation":{},"ISSN":["2690-442X"],"issn-type":[{"value":"2690-442X","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026,10]]},"published":{"date-parts":[[2026,8,3]]}}}