Walter MassonPablo CorralJuan P NogueiraAugusto Lavalle-Cobo2026-08-252026-08-252023-12-19http://repositorio.uia.ac.cr/handle/123456789/5135Artificial intelligence (AI) has rapidly expanded its applications in medicine, including clinical lipidology. This narrative review examines the potential uses of AI, machine learning (ML), and deep learning (DL) in the diagnosis, prediction, and management of lipid disorders. Relevant studies were identified through searches of major scientific databases. Current applications include familial hypercholesterolemia detection, low-density lipoprotein cholesterol estimation, prediction of lipid goal attainment, identification of barriers to statin use, and assessment of lipid discordance. AI-based approaches show promising diagnostic and predictive performance. However, ethical concerns, transparency, reproducibility, methodological limitations, and population-specific applicability require further research and appropriate regulatory frameworks.enArticle