Personalized caries prevention using AI-driven salivary microbiome analysis integrated with wearable dietary monitoring.

Abstract

Dental caries remains one of the most prevalent chronic oral diseases worldwide despite significant advances in preventive dentistry. Conventional preventive approaches often rely on generalized risk assessments that may not adequately account for individual variations in oral microbiology, dietary habits, and host responses. The convergence of artificial intelligence (AI), salivary microbiome analysis, and wearable dietary monitoring offers a transformative strategy for personalized caries prevention. AI algorithms can process complex salivary microbiome profiles, salivary biomarkers, and behavioral data collected through wearable biosensors to identify individualized caries risk patterns with greater accuracy than traditional methods. Continuous monitoring of dietary sugar intake, eating frequency, and oral environmental changes enables real-time assessment of factors that influence cariogenic activity, facilitating timely preventive interventions and personalized clinical recommendations. Integrating these technologies supports precision dentistry by improving early risk prediction, enhancing patient engagement, promoting preventive behavioral modifications, and optimizing evidence-based decision-making. Furthermore, remote monitoring capabilities expand access to preventive oral healthcare while supporting long-term disease surveillance and individualized treatment planning. Although challenges related to data integration, standardization, privacy, clinical validation, and implementation remain, AI-driven salivary microbiome analysis combined with wearable dietary monitoring represents a promising framework for advancing personalized, preventive, and predictive dental care