| Autor: |
Muñoz-López, C. Ramírez-Cornejo, C. Marchetti, M.A. Han, S.S. Del Barrio-Díaz, P. Jaque, A. Uribe, P. Majerson, D. Curi, M. Del Puerto, C. Reyes-Baraona, F. Meza-Romero, R. Parra-Cares, J. Araneda-Ortega, P. Guzmán, M. Millán-Apablaza, R. Nuñez-Mora, M. Liopyris, K. Vera-Kellet, C. Navarrete-Dechent, C. |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Popis: |
Background: The use of artificial intelligence (AI) algorithms for the diagnosis of skin diseases has shown promise in experimental settings but has not been yet tested in real-life conditions. Objective: To assess the diagnostic performance and potential clinical utility of a 174-multiclass AI algorithm in a real-life telemedicine setting. Methods: Prospective, diagnostic accuracy study including consecutive patients who submitted images for teledermatology evaluation. The treating dermatologist chose a single image to upload to a web application during teleconsultation. A follow-up reader study including nine healthcare providers (3 dermatologists, 3 dermatology residents and 3 general practitioners) was performed. Results: A total of 340 cases from 281 patients met study inclusion criteria. The mean (SD) age of patients was 33.7 (17.5) years; 63% (n = 177) were female. Exposure to the AI algorithm results was considered useful in 11.8% of visits (n = 40) and the teledermatologist correctly modified the real-time diagnosis in 0.6% (n = 2) of cases. The overall top-1 accuracy of the algorithm (41.2%) was lower than that of the dermatologists (60.1%), residents (57.8%) and general practitioners (49.3%) (all comparisons P |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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