Published Paper Details:

Cardiovascular diseases (CVDs) remain a leading cause of mortality worldwide, necessitating accurate and timely diagnosis for effective management and prevention. The integration of artificial intelligence (AI) techniques holds promise in enhancing the precision and efficiency of CVD diagnosis. This abstract outlines the framework and significance of employing AI in CVD diagnosis for a comprehensive project. The proposed project aims to develop and implement an AI-driven system for the diagnosis of cardiovascular diseases. Leveraging machine learning algorithms, particularly deep learning models, the system will analyze diverse patient data, including medical history, vital signs, imaging results, and genetic markers. Through the integration of these heterogeneous data sources, the AI model will learn complex patterns and relationships indicative of CVD presence, progression, and risk factors. Furthermore, the project will emphasize interpretability and transparency, providing clinicians with insights into the decision-making process of the AI model. The deployment of the AI-driven CVD diagnosis system in clinical settings has the potential to revolutionize cardiovascular healthcare delivery.