AI-Driven Dental Caries Management Strategies: From Clinical Practice to Professional Education and Public Self Care.

AI-Driven Dental Caries Management Strategies: From Clinical Practice to Professional Education and Public Self Care.

Liang, Yutong; Li, Dongling; Deng, Dongmei; Chu, Chun Hung; Mei, May Lei; Li, Yunpeng; Yu, Na; He, Jinzhi; Cheng, Lei
international dental journal 2025 Vol. 75 pp. 100827
24
liang2025aidriven

Abstract

Dental caries is one of the most prevalent chronic diseases among both children and adults, despite being largely preventable. This condition has significant negative impacts on human health and imposes a substantial economic burden. In recent years, scientists and dentists have increasingly started to utilize artificial intelligence (AI), particularly machine learning, to improve the efficiency of dental caries management. This study aims to provide an overview of the current knowledge about the AI-enabled approaches for dental caries management within the framework of personalized patient care. Generally, AI works as a promising tool that can be used by both dental professionals and patients. For dental professionals, it predicts the risk of dental caries by analyzing dental caries risk and protective factors, enabling to formulate personalized preventive measures. AI, especially those based on machine learning and deep learning, can also analyze images to detect signs of dental caries, assist in developing treatment plans, and help to make a risk assessment for pulp exposure during treatment. AI-powered tools can also be used to train dental students through simulations and virtual case studies, allowing them to practice and refine their clinical skills in a risk-free environment. Additionally, AI tracks brushing patterns and provides feedback to improve oral hygiene practices of the patients and the general population, thereby improving their understanding and compliance. This capability of AI can inform future research and the development of new strategies for dental caries management and control.

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283203
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10.1016/j.identj.2025.04.007
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