THEORETICAL AND SCIENTIFIC FOUNDATIONS FOR USAGE OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN DIAGNOSING AND TREATING CARDIOMYOPATHIES.

This paper explores the transformative potential and clinical hurdles of integrating Artificial Intelligence (AI) into the management of cardiomyopathies. While neural networks demonstrate remarkable precision in analyzing echocardiographic patterns and cardiac MRI, their transition from laboratory settings to bedside practice remains complex. We examine the "black box" phenomenon  where algorithmic logic remains opaque to clinicians and the ethical imperatives of automated decision-making. By synthesizing recent breakthroughs with the practicalities of digital cardiology, this study argues for a hybrid model where AI functions as a sophisticated clinical partner rather than a diagnostic replacement, specifically bridging the gap between standardized protocols and personalized patient care.