Today, the need for effective and cutting-edge methods of diagnosis, treatment, and prevention of cardiovascular diseases is greater than ever before because it is the top cause of death worldwide. Integrating deep learning and artificial intelligence into digital healthcare and medical environments has the potential to revolutionize cardiovascular health. The new book, Advances in Artificial Intelligence for Cardiovascular Disease: Diagnosis, Treatment, and Future Perspectives, addresses this need by discussing emerging uses of artificial intelligence (AI) and machine learning (ML) in the prediction, diagnosis, treatment, and management of cardiovascular diseases.

Divided into seven chapters, each chapter explores distinct facets of AI’s integration with cardiovascular disease management. The book provides an overview of AI’s core ideas and its vital roles in cardiovascular medicine, exploring the areas of machine learning and deep learning and its uses in healthcare and digital medical contexts. It looks at the world of wearable technology and how it interacts with AI algorithms. It also observes the function of cardiac imaging with an emphasis on nuclear cardiology, coronary CT angiography, and non-contrast cardiac CT methods that have the potential to completely change the way cardiovascular illness is diagnosed. It also explores the application of machine learning techniques in predicting and diagnosing cardiovascular diseases, revealing the potential for data-driven predictions and decisions that can improve patient outcomes. It also explores the potential of AI in a variety of cardiology applications, including the classification of ECG signals, wearables with AI support, and speech technologies in clinical settings. The book investigates the use of IoT and mobile health technologies to implement AI in the diagnosis of cardiovascular disease. Big data and AI’s capacity to forecast the dangers of cardiovascular diseases are also covered.

The book addresses contemporary difficulties and challenges in the management of cardiovascular illnesses by focusing on the therapeutic implications of deep learning and biomarker identification utilizing AI approaches. The presented insights will motivate researchers, medical professionals, and tech enthusiasts to embrace AI’s transformative potential in cardiovascular healthcare.