Artificial Intelligence as a Prognostic Tool in Cardiac Amyloidosis: A Review

Cardiac amyloidosis (CA) poses a significant prognostic challenge due to its varied presentations and frequent delays in identification. While traditional prognosticators, such as cardiac biomarkers and imaging parameters, offer valuable information, there are significant challenges with individualizing prognosis and accounting for its complex and heterogeneous nature. Artificial intelligence (AI) has enhanced the precision across multiple modalities and has emerged as a prognostic tool in cardiac amyloidosis, demonstrated through models that predict disease progression and stratify patient risk, often outperforming or complementing traditional staging systems. Utilizing AI-derived prognostic information ultimately facilitates informed decision-making-including early initiation of treatments, referrals to specialized centers, and planning for advanced therapies-thereby improving patient outcomes in cardiac amyloidosis. This review aims to synthesize the current advancements and applications of artificial intelligence in predicting outcomes and guiding management strategies for cardiac amyloidosis.