TY - JOUR
T1 - Artificial Intelligence–Powered Strategies for Smart Skin Scarring Management
AU - Wang, Zixin
AU - Zhang, Hanrui
AU - Liu, Yunhan
AU - Sun, Yingfei
AU - Xia, Wenzheng
AU - Zhao, Yixuan
AU - Gao, Yashan
AU - Lin, Yucong
AU - Huang, Xin
AU - Zan, Tao
N1 - Publisher Copyright:
Copyright © 2025 Zixin Wang et al. Dermatologic Therapy published by John Wiley & Sons Ltd.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - artificial intelligence
KW - convolutional neural networks
KW - deep learning
KW - skin scarring
UR - https://www.scopus.com/pages/publications/105026632582
U2 - 10.1155/dth/2874866
DO - 10.1155/dth/2874866
M3 - Review article
AN - SCOPUS:105026632582
SN - 1396-0296
VL - 2025
JO - Dermatologic Therapy
JF - Dermatologic Therapy
IS - 1
M1 - 2874866
ER -