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Khryanin A.A.

Novosibirsk State Medical University;
Association of obstetrician-gynecologists and dermatologists

Bocharova V.K.

Pavlov First Saint Petersburg State Medical University

Artificial intelligence in dermatology: opportunities and prospects

Authors:

Khryanin A.A., Bocharova V.K.

More about the authors

Journal: Russian Journal of Clinical Dermatology and Venereology. 2024;23(3): 246‑252

DOI: 10.17116/klinderma202423031246

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Table of contents

ARTIFICIAL INTELLIGENCE IN DERMATOLOGY: OPPORTUNITIES AND PROSPECTS
ARTIFICIAL INTELLIGENCE IN DERMATOLOGY: OPPORTUNITIES AND PROSPECTS

To cite this article:

Khryanin AA, Bocharova VK. Artificial intelligence in dermatology: opportunities and prospects. Russian Journal of Clinical Dermatology and Venereology. 2024;23(3):246‑252. (In Russ.)
https://doi.org/10.17116/klinderma202423031246

 
Подписка 2026 Клиническая дерматология и венерология (Russian Journal of Clinical Dermatology and Venereology)
 
МСФ на ЯМ
Использование инфографики авторами научных работ
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Abstract:

Artificial intelligence (AI) is becoming the most discussed technology in the world in recent years. AI based on neural network models makes significant progress in teledermatology. The problem is of critical importance and relevance, because telemedicine and AI, which are used in dermatology, make it possible to improve both the quality of health care for the population and the working process of medical professionals. The authors present a modern review of opportunities, prospects and problems related to the AI integration into the dermatologist’s clinical practice. For example, non-melanoma skin cancers (NMSCs) are known to be the most common cancers in the world, and melanoma is the most malignant form of skin cancer. Dermoscopy has increased the accuracy of NMSCs diagnosis by doctors, but, unfortunately, it remains relatively low. AI could provide invaluable help in early assessment and diagnosis of NMSCs. Studies have found that convolution neural network algorithms can classify skin lesions by dermoscopic images with very high or at least equivalent performance compared to clinicians. In this case, qualitative data and specialist’s feedback lead to a significant quality leap in the AI model. Nevertheless, despite the advantages and development speed of AI-based technologies, there are problems related to: a) the need to improve cybersecurity; b) the need to pay more attention to medico-legal and ethical issues; c) The need to standardize international and local regulations. The objective of the review article is to provide an analysis of the current achievements and limitations of AI in dermatology, paying special attention to the relevance of application in clinical practice.

Keywords:

artificial intelligence
machine learning
teledermatology
dermoscopy
skin cancers
melanoma
diagnosis
prevention

Authors:

Khryanin A.A.

Novosibirsk State Medical University;
Association of obstetrician-gynecologists and dermatologists

Bocharova V.K.

Pavlov First Saint Petersburg State Medical University

Received:

06.08.2023

Accepted:

13.03.2024

Close metadata

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