eISSN: 2299-0046
ISSN: 1642-395X
Advances in Dermatology and Allergology/Postępy Dermatologii i Alergologii
Current issue Archive Manuscripts accepted About the journal Editorial board Journal's reviewers Abstracting and indexing Subscription Contact Instructions for authors
SCImago Journal & Country Rank
5/2021
vol. 38
 
Share:
Share:
more
 
 
abstract:
Original paper

Evaluation of a smartphone application for diagnosis of skin diseases

Maksym Mikołajczyk
1
,
Sebastian Patrzyk
2
,
Mariusz Nieniewski
3
,
Anna Woźniacka
2

1.
Student Research Circle at the Department of Dermatology and Venereology, Medical University of Lodz, Lodz, Poland
2.
Department of Dermatology and Venereology, Medical University of Lodz, Lodz, Poland
3.
Faculty of Mathematics and Informatics, University of Lodz, Lodz, Poland
Adv Dermatol Allergol 2021; XXXVIII (5): 761-766
Online publish date: 2021/11/05
View full text
Get citation
ENW
EndNote
BIB
JabRef, Mendeley
RIS
Papers, Reference Manager, RefWorks, Zotero
AMA
APA
Chicago
Harvard
MLA
Vancouver
 
Introduction
Artificial intelligence (AI) could offer equal, or even more accurate, diagnoses of melanoma than most dermatologists. However, the value of popular smartphone applications for diagnosing unpigmented skin lesions remains unclear.

Aim: To compare the diagnostic accuracy of a popular, free-to-use web application for automatic dermatosis diagnosis against expert diagnosis of selected skin diseases.

Material and methods
Skin lesion images of patients with verified diagnosis were collected using a smartphone and were diagnosed by the application. The AI provided five diagnoses of varying probability. For each patient, accuracy of the diagnosis was evaluated by three criteria, i.e. whether the expert diagnosis was matched by the most probable automated diagnosis, one of the top three diagnoses or one of the top five diagnoses. Reliability was analysed using intraclass correlation coefficients.

Results
The chance of a correct diagnosis increased when more outcomes were considered and more samples of a skin condition were included. However, the probability of a diagnosis repeating for the same patient was below 25%. Reliability, sensitivity and specificity were insufficient for clinical purposes.

Conclusions
Although AI diagnostics are encouraging, there is also a large margin for improvement, and AI is not yet an adequate replacement for medical professionals.

keywords:

artificial intelligence, smartphone application, web application, skin diseases diagnosis, psoriasis, new technology

Quick links
© 2021 Termedia Sp. z o.o. All rights reserved.
Developed by Bentus.