Integration of Machine Learning and Optimization Techniques for Cardiac Health Recognition

Cardiovascular disease (CVD) remains the primary reason for illness and death throughout the world despite tremendous progress in diagnosis and treatment. Artificial intelligence (AI) technology can drastically revolutionize the way we perform cardiology to enhance and optimize CVD results. With boosting of information technology and the increased volume and complexity of data, aside from a large number of optimization problems that arise in clinical fields, AI approaches such as machine learning and optimization have become extremely popular. AI also can help improve medical expertise by uncovering clinically important information. Early on, the treatment of vast amounts of medical data was a significant task, leading to adaptations in the biological field of machine learning. Improvements are carried out and tested every day in algorithms for machine learning so that more accurate data may be analyzed and provided. Machine learning has been active in the realm of healthcare, from the extraction of information from medical papers to the prediction and diagnosis of a disease. In this perspective, this chapter provides an overview of how to use meta-heuristic algorithm on CVD’s classification process for enhancing feature selection process, and various parameters optimization.