Artificial intelligence automates imaging analysis, quantifies cardiac anatomy, and assesses hemodynamics with greater accuracy, efficiency, and reproducibility than conventional methods.
Artificial intelligence is emerging as a complementary tool to support clinical decision making, diagnosis, procedural planning, and outcome prediction in structural heart disease.
Transcatheter cardiac interventions have advanced substantially over the past decade, providing less invasive therapeutic options for an expanding spectrum of structural heart disease.As procedural complexity increases, artificial intelligence (AI) has emerged as a complementary tool to support clinical decision making.Early studies demonstrated that AI can automate imaging analysis, quantify cardiac anatomy, and assess hemodynamics with greater accuracy, efficiency, and reproducibility than conventional methods.This comprehensive review summarizes current clinical applications of AI in structural heart disease, focusing on its role in diagnosis, assessment of disease progression, risk stratification, procedural planning, and prediction of clinical outcomes.
Allaham et al. (Sun,) conducted a review in Structural heart disease. Artificial intelligence (AI) vs. Conventional methods was evaluated. Artificial intelligence automates imaging analysis, quantifies cardiac anatomy, and assesses hemodynamics with greater accuracy, efficiency, and reproducibility than conventional methods.