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In Journal of the European Academy of Dermatology and Venereology : JEADV

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 in real-life conditions.

OBJECTIVE : To assess the diagnostic performance and potential clinical utility of an 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, 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 12% 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<0.05, in the reader study). When the analysis was limited to the diagnoses on which the algorithm had been explicitly trained, the balanced top-1 accuracy of the algorithm (47.6%) was comparable to the dermatologists (49.7%) and residents (47.7%) but superior to the general practitioners (39.7%; p=0.049). Algorithm performance was associated with patient skin type and image quality.

CONCLUSIONS : A 174-disease class AI algorithm appears to be a promising tool in the triage and evaluation of lesions with patient-taken photos via telemedicine.

Muñoz-López Camila, Ramírez-Cornejo Cristian, Marchetti Michael A, Han Seung Seog, Del Barrio-Díaz Pablo, Jaque Alejandra, Uribe Pablo, Majerson Daniela, Curi Maximiliano, Del Puerto Constanza, Reyes-Baraona Francisco, Meza-Romero Rodrigo, Parra-Cares Julio, Araneda-Ortega Paulina, Guzmán Mariana, Millán-Apablaza Rocío, Nuñez-Mora Marcelo, Liopyris Konstantinos, Vera-Kellet Cristián, Navarrete-Dechent Cristian