Enhancing Diagnostic Accuracy and Procedural Outcomes in Interventional Cardiology Through Machine Learning Algorithms

In the rapidly evolving landscape of interventional cardiology, the advent of artificial intelligence (AI) and machine learning (ML) heralds a transformative era. Interventional cardiologists are now at the cusp of a significant shift in their practice, driven by 2 pivotal trends. First, AI's capability to uncover more subclinical diseases is enhancing the diagnostic value of intravascular imaging modalities such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT), improving preprocedural planning for complex coronary and structural interventions.