Evaluation of the Diagnostic Accuracy of an Online Artificial Intelligence Application for Skin Disease Diagnosis.
dermatology
online diagnostics
skin disease
artificial intelligence
Journal
Acta dermato-venereologica
ISSN: 1651-2057
Titre abrégé: Acta Derm Venereol
Pays: Sweden
ID NLM: 0370310
Informations de publication
Date de publication:
16 Sep 2020
16 Sep 2020
Historique:
pubmed:
28
8
2020
medline:
24
6
2021
entrez:
28
8
2020
Statut:
epublish
Résumé
Artificial intelligence (AI) algorithms for automated classification of skin diseases are available to the consumer market. Studies of their diagnostic accuracy are rare. We assessed the diagnostic accuracy of an open-access AI application (Skin Image Search™) for recognition of skin diseases. Clinical images including tumours, infective and inflammatory skin diseases were collected at the Department of Dermatology at the Sahlgrenska University Hospital and uploaded for classification by the online application. The AI algorithm classified the images giving 5 differential diagnoses, which were then compared to the diagnoses made clinically by the dermatologists and/or histologically. We included 521 images portraying 26 diagnoses. The diagnostic accuracy was 56.4% for the top 5 suggested diagnoses and 22.8% when only considering the most probable diagnosis. The level of diagnostic accuracy varied considerably for diagnostic groups. The online application demonstrated low diagnostic accuracy compared to a dermatologist evaluation and needs further development.
Identifiants
pubmed: 32852557
doi: 10.2340/00015555-3624
pmc: PMC9234984
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
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