KI-Caries-Tool

Development of an AI Tool for Assessing Approximal Caries Progression Risk: A Machine Learning and Retrospective Study at Tübingen Dental School

01.09.2025 bis 31.08.2027

Approximal caries is a highly prevalent dental issue that often progresses undetected, leading to the need for invasive treatments. In order to improve the understanding of early detection and prediction of approximal caries progression, a study based on real clinical data is designed in two phases: Phase 1 retrospectively examines initial caries lesions and risk factors associated with caries progression in a cohort of patients examined over the last twelve years in the University Hospital of Tübingen. Phase 2 aims to develop and validate an artificial intelligence (AI) tool using machine learning algorithms to both detect and predict caries progression risk based on individual patient data, enhancing clinical decision-making in dental practice.