Artificial Intelligence Application and Future Directions in Infiltrative and Inflammatory Cardiomyopathies: A State-of-the-Art Review.

Infiltrative and inflammatory cardiomyopathies carry substantial morbidity and mortality. Nonspecific clinical presentations can delay recognition; prognostic tools are limited. Artificial intelligence (AI) can mine clinical, imaging, biomarker, and histologic data to reveal multidimensional patterns beyond conventional interpretation. In infiltrative cardiomyopathies, early applications have concentrated on cardiac amyloidosis, with emerging work in Fabry disease and myocardial iron overload. For inflammatory cardiomyopathies, early studies suggest roles for AI-enhanced electrocardiography and imaging in detection, prognosis, and guidance for therapy. Evidence remains largely single-center, retrospective, and small, with heterogeneous comparators and risks of circularity, limiting generalizability. Ethical, regulatory, and implementation barriers also impede adoption. AI's likely value is in complementing clinical judgment by flagging subtle signals that deserve attention and in nudging clinicians toward earlier or more focused testing. In this review, we outline recent progress, reflect on the barriers that remain, and consider how these tools might eventually be woven into everyday care.