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dc.rights.licenseopenen_US
dc.contributor.authorHILLMER, Dirk
hal.structure.identifierImmunology from Concept and Experiments to Translation = Immunologie Conceptuelle, Expérimentale et Translationnelle [ImmunoConcept]
dc.contributor.authorMERHI, Ribal
hal.structure.identifierImmunology from Concept and Experiments to Translation = Immunologie Conceptuelle, Expérimentale et Translationnelle [ImmunoConcept]
dc.contributor.authorBONIFACE, Katia
IDREF: 10566913X
dc.contributor.authorTAIEB, Alain
dc.contributor.authorBARNETCHE, Thomas
hal.structure.identifierImmunology from Concept and Experiments to Translation = Immunologie Conceptuelle, Expérimentale et Translationnelle [ImmunoConcept]
dc.contributor.authorSENESCHAL, Julien
dc.contributor.authorHAGEDORN, Martin
dc.date.accessioned2025-01-30T08:42:21Z
dc.date.available2025-01-30T08:42:21Z
dc.date.issued2024-02
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/204655
dc.description.abstractEnVitiligo is the most common depigmenting skin disorder. Given the ongoing development of new targeted therapies, it has become important to evaluate adequately the surface area involved. Assessment of vitiligo scores can be time consuming, with variations between investigators. Therefore, the aim of this study was to build an artificial intelligence system capable of assessing facial vitiligo severity. One hundred pictures of faces of patients with vitiligo were used to train and validate the artificial intelligence model. Sixty-nine additional pictures of facial vitiligo were then used as a final dataset. Three expert physicians scored the facial vitiligo on the same 69 pictures. Inter and intrarater performances were evaluated by comparing the scores between raters and artificial intelligence. Algorithm assessment achieved an accuracy of 93%. Overall, the scores reached a good agreement between vitiligo raters and the artificial intelligence model. Results demonstrate the potential of the model. It provides an objective evaluation of facial vitiligo and could become a complementary/alternative tool to human assessment in clinical practice and/or clinical research.
dc.language.isoENen_US
dc.title.enEvaluation of Facial Vitiligo Severity with a Mixed Clinical and Artificial Intelligence Approach
dc.typeArticle de revueen_US
dc.identifier.doi10.1016/j.jid.2023.07.014en_US
dc.subject.halSciences du Vivant [q-bio]/Immunologieen_US
dc.identifier.pubmed37586608en_US
bordeaux.journalJournal of Investigative Dermatologyen_US
bordeaux.page351 – 357.e4en_US
bordeaux.volume144en_US
bordeaux.hal.laboratoriesImmunoConcEpT - UMR 5164en_US
bordeaux.issue2en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionCNRSen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-04920316
hal.version1
hal.date.transferred2025-01-30T08:42:24Z
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exporttrue
dc.rights.ccPas de Licence CCen_US
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