Artificial Intelligence in Valvular Heart Disease: Current Applications and Future Perspectives

Valvular heart disease (VHD) remains a major contributor to global cardiovascular morbidity and mortality, with diagnosis and management relying on complex multimodality imaging and expert interpretation. This narrative review aims to evaluate the current applications and future potential of artificial intelligence (AI) in VHD. A comprehensive literature search was conducted using major databases, including PubMed, Scopus, and Web of Science, focusing on studies published in English that examined AI applications in VHD diagnosis, procedural planning, intraprocedural guidance, and prognostic assessment. Relevant original studies, clinical trials, and review articles were included based on their methodological quality and clinical relevance. Current evidence indicates that AI enhances early detection through accessible modalities such as electrocardiography and chest radiography, while significantly improving the accuracy and reproducibility of echocardiographic assessment. AI also facilitates precise preprocedural planning for transcatheter interventions and offers real-time support during procedures through multimodal image integration. In addition, AI-driven models enable robust risk stratification and prediction of clinical outcomes. Emerging innovations, including in silico trials and robotic-assisted interventions, further highlight AI’s transformative potential. Despite these advances, challenges related to data quality, bias, interpretability, and regulatory oversight remain. Continued validation and integration are essential to realize AI-driven precision medicine in VHD.