AI and ML are reshaping echocardiography by automating analysis and improving diagnostic accuracy, despite ongoing challenges with clinical integration.
Artificial intelligence (AI) and machine learning (ML) are reshaping echocardiography by automating image analysis, reducing variability, and enhancing diagnostic accuracy through tasks such as view classification, image segmentation, and outcome prediction. Key applications include left ventricular ejection fraction assessment and improved valvular disease diagnostics. Limitations include challenges with generalizability, interpretability, and integration into diverse clinical settings. This article provides a contemporary review of AI and ML applications in echocardiography.
Raissi-Dehkordi et al. (Thu,) studied this question.