Content » Vol 100, September

Investigative Report

Evaluation of the Diagnostic Accuracy of an Online Artificial Intelligence Application for Skin Disease Diagnosis

Oscar Zaar, Alexander Larson, Sam Polesie, Karim Saleh, Mikael Tarstedt, Antonio Olives, Andrea Suárez, Martin Gillstedt, Noora Neittaanmäki
DOI: 10.2340/00015555-3624


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.


In research settings, artificial intelligence (AI) algorithms for automated classification of skin diseases have shown promising results with a diagnostic accuracy that have performed equal to or even outperformed dermatologists. Similar online AI applications are available to the consumer market, readily accessible to anyone with a smartphone. Nevertheless, external and independent validation investigations of the diagnostic accuracy of these applications are lacking. The studied AI application achieved an unsatisfactory overall diagnostic accuracy. The level of diagnostic accuracy varied greatly for diagnostic groups as well as for individual diagnoses. Online automated classification systems should be further developed to ensure appropriate accuracy.

Supplementary content


Not logged in! You need to login/create an account to comment on articles. Click here to login/create an account.