A Study Of Deep Learning For Echo Analysis, Tracking, And Evaluation

The purpose of this study is to deploy and evaluate informational AI-Echo algorithms that assist echo clinicians in interpreting core echocardiographic parameters (e.g., LV/RV size and function, valvular disease severity) and stratifying disease progression risk. The primary outcome is clinician usability, interpretive consistency, and workflow integration. Second, we will conduct a pragmatic, stepped-wedge clinical trial with multiple arms evaluating diagnostic AI-Echo algorithms designed to identify specific cardiovascular diseases- such as genetic cardiomyopathy, ischemic heart disease, and cardiac amyloidosis-and assess whether AI deployment increases diagnostic testing and shortens time to diagnosis. Trials will be conducted using EHR-based notification systems with cluster-level randomization.