Artificial Intelligence–Powered Strategies for Smart Skin Scarring Management

  • Zixin Wang
  • , Hanrui Zhang
  • , Yunhan Liu
  • , Yingfei Sun
  • , Wenzheng Xia
  • , Yixuan Zhao
  • , Yashan Gao
  • , Yucong Lin*
  • , Xin Huang*
  • , Tao Zan*
  • *Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

Skin scarring is a significant dermatological condition that profoundly impacts patients both physically and mentally, contributing to a substantial global disease burden. However, current management is hindered by several challenges, including subjective differential diagnosis, inconsistent disease assessment, a lack of targeted therapies, suboptimal treatment efficacy, and high recurrence rates. The rise of artificial intelligence (AI) has already proven to be a game changer in numerous areas of healthcare. This review comprehensively explores AI-driven advancements in current skin scarring management, including but not limited to precise diagnosis, automated severity assessment, AI-assisted surgical interventions, smart posttreatment monitoring, and new drug development. Additionally, AI-based virtual consultations and personalized treatment algorithms hold great potential for improving patient-centered care. Ultimately, we propose a multimodal AI-driven scar management system featuring an upstream “data harbor” public platform and downstream validations for personalized diagnosis and treatment, enhancing the intelligent optimization of clinical practices in skin-scarring management.

Original languageEnglish
Article number2874866
JournalDermatologic Therapy
Volume2025
Issue number1
DOIs
Publication statusPublished - 2025
Externally publishedYes

Keywords

  • artificial intelligence
  • convolutional neural networks
  • deep learning
  • skin scarring

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