{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T16:02:04Z","timestamp":1784390524506,"version":"3.55.0"},"reference-count":11,"publisher":"Elsevier BV","issue":"5","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,7,12]],"date-time":"2025-07-12T00:00:00Z","timestamp":1752278400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Anais Brasileiros de Dermatologia"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1016\/j.abd.2025.501169","type":"journal-article","created":{"date-parts":[[2025,8,13]],"date-time":"2025-08-13T12:22:05Z","timestamp":1755087725000},"page":"501169","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":2,"title":["Artificial intelligence for the diagnosis of erythematous-squamous dermatological diseases: technological contributions to primary care"],"prefix":"10.1016","volume":"100","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-8843-4366","authenticated-orcid":false,"given":"Raiza","family":"Brito Cipriano","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8292-0526","authenticated-orcid":false,"given":"Wilson","family":"Falco Neto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1491-2700","authenticated-orcid":false,"given":"Fabiano N.","family":"Barcellos Filho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3251-9600","authenticated-orcid":false,"given":"Alexandre","family":"Dias Porto Chiavegatto Filho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.abd.2025.501169_bib0005","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1111\/j.1440-0960.2005.00189.x","article-title":"Assessing diagnostic skill in dermatology: a comparison between general practitioners and dermatologists","volume":"46","author":"Tran","year":"2005","journal-title":"Australas J Dermatol."},{"key":"10.1016\/j.abd.2025.501169_bib0010","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1001\/archderm.137.12.1627","article-title":"A comparison of dermatologists\u2019 and primary care physicians\u2019 accuracy in diagnosing melanoma: a systematic review","volume":"137","author":"Chen","year":"2001","journal-title":"Arch Dermatol."},{"key":"10.1016\/j.abd.2025.501169_bib0015","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1007\/s13555-020-00372-0","article-title":"Machine learning in dermatology: current applications, opportunities, and limitations","volume":"10","author":"Chan","year":"2020","journal-title":"Dermatol Ther (Heidelb)."},{"key":"10.1016\/j.abd.2025.501169_bib0020","author":"Ilter"},{"key":"10.1016\/j.abd.2025.501169_bib0025","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1038\/s42256-019-0138-9","article-title":"From local explanations to global understanding with explainable AI for trees","volume":"2","author":"Lundberg","year":"2020","journal-title":"Nat Mach Intell."},{"key":"10.1016\/j.abd.2025.501169_bib0030","series-title":"Interpretable machine learning: A guide for making black box models explainable","author":"Molnar","year":"2022"},{"key":"10.1016\/j.abd.2025.501169_bib0035","doi-asserted-by":"crossref","first-page":"338","DOI":"10.5455\/aim.2016.24.338-342","article-title":"Differential diagnosis of erythmato-squamous diseases using classification and regression tree","volume":"24","author":"Maghooli","year":"2016","journal-title":"Acta Inform Med."},{"key":"10.1016\/j.abd.2025.501169_bib0040","series-title":"Proceedings of the 2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","first-page":"1","article-title":"A hybrid deep learning approach for diagnosis of the Erythemato-Squamous disease","author":"Putatunda","year":"2020"},{"key":"10.1016\/j.abd.2025.501169_bib0045","series-title":"StatPearls [Internet]","article-title":"Pityriasis Rubra Pilaris","author":"Greiling","year":"2024"},{"key":"10.1016\/j.abd.2025.501169_bib0050","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1016\/j.autrev.2014.01.008","article-title":"Diagnosis and classification of psoriasis","volume":"13","author":"Raychaudhuri","year":"2014","journal-title":"Autoimmun Rev."},{"key":"10.1016\/j.abd.2025.501169_bib0055","doi-asserted-by":"crossref","first-page":"3343","DOI":"10.1038\/s41598-021-82885-y","article-title":"A multipurpose machine learning approach to predict COVID-19 negative prognosis in S\u00e3o Paulo, Brazil","volume":"11","author":"Fernandes","year":"2021","journal-title":"Sci Rep."}],"container-title":["Anais Brasileiros de Dermatologia"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0365059625001114?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0365059625001114?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T18:13:02Z","timestamp":1758910382000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0365059625001114"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":11,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["S0365059625001114"],"URL":"https:\/\/doi.org\/10.1016\/j.abd.2025.501169","relation":{},"ISSN":["0365-0596"],"issn-type":[{"value":"0365-0596","type":"print"}],"subject":[],"published":{"date-parts":[[2025,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Artificial intelligence for the diagnosis of erythematous-squamous dermatological diseases: technological contributions to primary care","name":"articletitle","label":"Article Title"},{"value":"Anais Brasileiros de Dermatologia","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.abd.2025.501169","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Sociedade Brasileira de Dermatologia. Published by Elsevier Espa\u00f1a, S.L.U.","name":"copyright","label":"Copyright"}],"article-number":"501169"}}