Beyond the Stethoscope: Artificial Intelligence for Heart Failure Diagnosis and Phenotyping.

Abstract

Artificial intelligence (AI) is reshaping cardiovascular medicine by transforming routinely collected clinical data into tools for earlier disease detection and more precise phenotyping. Heart failure (HF) represents a particularly compelling opportunity for AI-driven innovation, as many patients with structural heart disease remain unrecognized and traditional diagnostic frameworks often fail to capture disease heterogeneity. AI-enabled electrocardiogram (ECG) models, including EchoNext and PRESENT-SHD, highlight the potential for scalable opportunistic screening strategies for structural heart disease. Multimodal approaches, using ECGs and echocardiograms, are enabling earlier recognition of specific HF phenotypes, such as transthyretin cardiac amyloidosis. Successful implementation of these technologies will require prospective evaluation, thoughtful workflow integration, and responsible deployment. Early-career cardiologists are uniquely positioned to lead this transformation of AI in clinical medicine, ensuring that AI serves as a tool to augment clinical reasoning and ultimately advances more personalized, patient-centered cardiovascular care.