AI-assisted facial analysis in healthcare: From disease detection to comprehensive management
Chaoyu Lei, Kang Dang, Sifan Song, Zilong Wang, Sien Ping Chew, Ruitong Bian, Xichen Yang, Zhouyu Guan, Marques de Abreu Lopes, Claudia, Mini Hang Wang, Richard Wai Chak Choy, Xiaoyan Hu, Kenneth Ka Hei Lai, Kelvin Kam Lung Chong, Chi Pui Pang, Xuefei Song, Jionglong Su, Xiaowei Ding and Huifang Zhou, (2025). AI-assisted facial analysis in healthcare: From disease detection to comprehensive management. Patterns, 6(2), n/a-n/a
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https://www.cell.com/patterns/fulltext/S2666-3899(25)00023-6 Link
http://dx.doi.org/https://doi.org/10.1016/j.patter.2025.101175 Full text from publisher -
Sub-type Journal article Author Chaoyu Lei
Kang Dang
Sifan Song
Zilong Wang
Sien Ping Chew
Ruitong Bian
Xichen Yang
Zhouyu Guan
Marques de Abreu Lopes, Claudia
Mini Hang Wang
Richard Wai Chak Choy
Xiaoyan Hu
Kenneth Ka Hei Lai
Kelvin Kam Lung Chong
Chi Pui Pang
Xuefei Song
Jionglong Su
Xiaowei Ding
Huifang ZhouTitle AI-assisted facial analysis in healthcare: From disease detection to comprehensive management Appearing in Patterns Volume 6 Issue No. 2 Publication Date 2025-02-14 Place of Publication Cambridge, Massachusetts, USA Publisher Cell Press Start page n/a End page n/a Language eng Abstract Medical conditions and systemic diseases often manifest as distinct facial characteristics, making identification of these unique features crucial for disease screening. However, detecting diseases using facial photography remains challenging because of the wide variability in human facial features and disease conditions. The integration of artificial intelligence (AI) into facial analysis represents a promising frontier offering a user-friendly, non-invasive, and cost-effective screening approach. This review explores the potential of AI-assisted facial analysis for identifying subtle facial phenotypes indicative of health disorders. First, we outline the technological framework essential for effective implementation in healthcare settings. Subsequently, we focus on the role of AI-assisted facial analysis in disease screening. We further expand our examination to include applications in health monitoring, support of treatment decision-making, and disease follow-up, thereby contributing to comprehensive disease management. Despite its promise, the adoption of this technology faces several challenges, including privacy concerns, model accuracy, issues with model interpretability, biases in AI algorithms, and adherence to regulatory standards. Addressing these challenges is crucial to ensure fair and ethical use. By overcoming these hurdles, AI-assisted facial analysis can empower healthcare providers, improve patient care outcomes, and enhance global health. Keyword Artificial Intelligence
Facial Analysis
Healthcare
Disease Screening
Global HealthCopyright Holder Authors Copyright Year 2025 Copyright type Creative commons DOI https://doi.org/10.1016/j.patter.2025.101175 -
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