The Role of Artificial Intelligence in Cardiac Amyloidosis: A Focus on Diagnosis and Clinical Application
Roshan Wardak, David Snipelisky
Abstract
The aim of this review is to provide an update on contemporary and evolving artificial intelligence (AI) methods and their role in diagnosing and managing cardiac amyloidosis (CA). AI is the broadest term which describes a variety of different techniques that enable computers to mimic human intelligence. It is widely used across different diagnostic tests including electrocardiograms, echocardiography, scintigraphy and cardiac magnetic resonance (CMR). Through a comprehensive search among four databases, we identified several insights into clinical applications, diagnostic modalities and different utilization of AI in CA. The elusive nature of CA, which often makes early diagnosis challenging, can greatly benefit from the integration of AI into the diagnostic process. The variability in diagnostic strategies of CA underscores the need for more AI-focused prospective clinical trials to establish evidence-based guidelines for AI-driven diagnostic pathways. Our review highlights the capabilities of AI, particularly in the diagnosis of cardiac amyloidosis.