Artificial intelligence applications relevant to infective endocarditis in an oral–systemic context: a scoping review

This project explores the applications of Artificial Intelligence (AI) in the prevention, early detection, diagnosis, and management of Infective Endocarditis (IE), particularly in cases originating from oral or dental infections. Infective Endocarditis remains a life-threatening disease often linked to oral microorganisms entering the bloodstream through dental infections or procedures. Despite this significant association, the integration of AI in studying and managing oral-origin IE has not been systematically mapped. This scoping review aims to identify, categorize, and synthesize existing evidence on how AI and machine learning models have been used to improve diagnostic accuracy, risk prediction, and clinical decision-making in IE. It will also highlight methodological trends, research gaps, and opportunities for future interdisciplinary collaboration among dentistry, cardiology, microbiology, and data science. The expected outcome of this project is to provide a comprehensive overview of current research efforts, summarize AI model performance in IE-related studies, and propose directions for future work that may enhance early detection and prevention strategies linking oral health and cardiovascular disease.