Position Statement on Echocardiography and Artificial Intelligence

Abstract

Echocardiography is a key tool in cardiac assessment but faces challenges such as subjectivity in interpretation and dependence on image quality. AI, through techniques like machine learning and deep learning, enables the automation of processes such as image acquisition, quantification of parameters (ejection fraction, ventricular volumes), and suspicion of pathologies (hypertrophic cardiomyopathy, cardiac amyloidosis). Additionally, AI facilitates medical education through simulations that provide real-time feedback. Despite its advantages, challenges remain, including the lack of transparency in algorithms ("black box"), the need for external validation, and dependence on image quality. In conclusion, AI will not replace echocardiographists but will become an indispensable tool for optimizing diagnosis and clinical decision-making.