Artificial Intelligence and digital assessment and Screening of Oral Frailty in Older Adults: A Scoping Review

Introduction: Oral frailty (OF) is increasingly recognized as a critical precursor to physical frailty, functional decline, and adverse health outcomes among older adults. Traditional assessment approaches often rely on trained professionals and clinical settings, which limits their scalability for large-scale community screening. Recent advances in artificial intelligence (AI) offer new opportunities for early, non-invasive screening of oral frailty in community-dwelling populations. Objectives: This scoping review aims to map the global evidence on the application of artificial intelligence for the diagnosis and screening of oral frailty in older adults aged 60 years and above. The review focuses on: (1) the diagnostic or screening frameworks used as reference standards within AI-based oral frailty studies; (2) the characteristics of study populations used for the development and validation of AI models, in order to assess their applicability to older adults; and (3) the types of AI-driven and digital assessment technologies designed for community settings, along with their reported performance metrics and practical feasibility. Methods: This scoping review will be conducted in accordance with the PRISMA-ScR guidelines. A comprehensive literature search will be performed in PubMed, Web of Science, Scopus, CINAHL, the Cochrane Library, J-STAGE, and the China National Knowledge Infrastructure (CNKI). Two reviewers will independently screen peer-reviewed empirical studies and extract relevant data. Findings will be synthesized descriptively to map existing evidence and identify research gaps.