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SYSTEMATIC REVIEW article

Front. Digit. Health

Sec. Health Technology Implementation

Volume 7 - 2025 | doi: 10.3389/fdgth.2025.1544520

This article is part of the Research TopicDigital Medicine and Artificial IntelligenceView all 4 articles

Advancements and Challenges of Artificial Intelligence in Dermatology: A Review of Applications and Perspectives in China

Provisionally accepted
  • 1Shanghai Jiao Tong University, Shanghai, Shanghai Municipality, China
  • 2International Agency For Research On Cancer (IARC), Lyon, France

The final, formatted version of the article will be published soon.

The diagnosis of skin diseases can be challenging due to their diverse manifestations, while early detection of malignant skin cancers greatly improves the prognosis, highlighting the pressing need for efficient screening methods. In recent years, advancements in AI have paved the way for AI-aided diagnosis of skin lesions. Furthermore, the COVID-19 pandemic has spurred the demand of telemedicine, accelerating the integration of AI into medical domains, particularly in China. This article aims to provide an overview of the progress of AIaided diagnosis in Chinese dermatology. Given the widespread use of public datasets in the reviewed studies, we compared the performance of AI models in segmentation and classification on public datasets. Despite the promising results of AI in experimental settings, we recognize the limitations of these public datasets in representing clinical scenarios in China.To address this gap, we reviewed the studies that used clinical datasets and conducted comparative analyses between AI and dermatologists. Although AI demonstrated comparable results to human experts, AI still cannot replace dermatologists due to limitations in generalizability and interpretability. We attempt to provide insights into improving the performance of AI through advancements in dataset quality, image pre-processing techniques, and integration of medical data. Finally, the role that AI will play in the medical practice and the relationship between AI and dermatologists are discussed. This systematic review addresses the gap in evaluating AI applications in Chinese dermatology, with a focus on dermatological datasets and real-world application.

Keywords: artificial intelligence, Dermatology, China, AI-aided diagnosis, machine learning

Received: 13 Dec 2024; Accepted: 21 Jul 2025.

Copyright: © 2025 Yu, Cheong, Kozlakidis and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Zisis Kozlakidis, International Agency For Research On Cancer (IARC), Lyon, France

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