Systematic Review of Obstacles to the Implementation of Artificial Intelligence in the Diagnosis of Cardiovascular Diseases in Latin America.

Abstract

This Systematic Literature Review (SLR) analyzes the obstacles to the implementation of artificial intelligence (AI) models in the diagnosis of cardiovascular diseases in Latin America. The results obtained have shown a significant growth in the number of publications in 2024, reflecting a growing interest and recent advances in AI adoption. The main obstacles identified are regulatory barriers (31%), lack of trained experts (25%), high costs (19%), difficulty in clinical validation (12%) and insufficient infrastructure (13%). Likewise, it is facing several key challenges, which are: Inequalities in access to advanced technologies and medical resources limit their adoption, especially in rural areas and disadvantaged communities. The variability and quality of medical data also present significant obstacles, hindering effective integration and analysis. In addition, the lack of adequate infrastructure and trained personnel exacerbates the situation. Finally, regulatory and ethical concerns, along with the need for clear policy frameworks, further hinder the effective implementation of AI in this region.