An AI Approach towards Cardiovascular Diseases: A Review

Cardiovascular diseases (CVDs) remains to be one of the concerns of mortality. There is an immense need of advanced tools for its efficacious prediction, its diagnosis, and management. Transformative potential of artificial intelligence is highlighted in this review, especially machine learning (ML) and deep learning (DL), in attending the challenges of traditional methods of diagnosis. It investigates the scope of types of CVD, its associated risk factors, and the extent of conventional approaches, indicating the ways computational models can improve precision and efficiency in cardiological cases. Key challenges such as data quality, interpretability, and implementation barriers are also discussed in this review highlighting the importance of integrating these technologies into clinical practice. By distinguishing areas for future investigation and analyzing recent modern innovations, this paper underlines the capacity of AI-driven solutions in revolutionizing cardiovascular care.