A Review of AI-Driven Digital Twin Frameworks for Cardiovascular Disease Diagnosis and Management

The combination of Artificial Intelligence (AI) and Digital Twin (DT) technologies in healthcare could revolutionize the administration and treatment of intricate conditions, including myocardial infarction and stroke. This study offers an extensive analysis of contemporary methodologies and examines the prospects of a conceptual AIdriven digital twin framework for healthcare applications. The proposed system integrates real-time data, machine learning algorithms, and sophisticated computational methods to improve diagnostic accuracy and refine treatment approaches. Although current literature illustrates the efficacy of AI and digital technologies in customized medicine, substantial obstacles persist in data integration, processing capacity, and ethical issues. This study clarifies the present condition of AIdriven digital twin technologies and delineates critical domains for prospective research and development. The objective is to create a basis for enhancing the incorporation of these technologies in healthcare to optimize patient outcomes and clinical decision-making.