This book provides a comprehensive guide to the state-of-the-art in cardiovascular computing and highlights novel directions and challenges in this constantly evolving multidisciplinary field. The topics covered span a wide range of methods and clinical applications of cardiovascular computing, including advanced technologies for the acquisition and analysis of signals and images, cardiovascular informatics, and mathematical and computational modeling.

This book provides a comprehensive guide to the state-of-the-art in cardiovascular computing and highlights novel directions and challenges in this constantly evolving multidisciplinary field. The topics covered span a wide range of methods and clinical applications of cardiovascular computing, including advanced technologies for the acquisition and analysis of signals and images, cardiovascular informatics, and mathematical and computational modeling.

Cardiovascular diseases (CVD) including heart diseases, peripheral vascular disease and heart failure, account for one-third of deaths throughout the world. CVD risk factors include systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, and diabetic status. Clinical trials have demonstrated that when modifiable risk factors are treated and corrected, the chances of CVD occurring can be reduced. This illustrates the importance of this book's elaborate coverage of cardiovascular physiology by the application of mathematical and computational methods.This book has literally transformed Cardiovascular Physiology into a STEM discipline, involving (i) quantitative formulations of heart anatomy and physiology, (ii) technologies for imaging the heart and blood vessels, (iii) coronary stenosis hemodynamics measure by means of fractional flow reserve and intervention by grafting and stenting, (iv) fluid mechanics and computational analysis of blood flow in the heart, aorta and coronary arteries, and (v) design of heart valves, percutaneous valve stents, and ventricular assist devices.So how is this mathematically and computationally configured landscape going to impact cardiology and even cardiac surgery? We are now entering a new era of mathematical formulations of anatomy and physiology, leading to technological formulations of medical and surgical procedures towards more precise medicine and surgery. This will entail reformatting of (i) the medical MD curriculum and courses, so as to educate and train a new generation of physicians who are conversant with medical technologies for applying into clinical care, as well as (ii) structuring of MD-PhD (Computational Medicine and Surgery) Program, to train competent medical and surgical specialists in precision medical care and patient-specific surgical care.This book provides a gateway for this new emerging scenario of (i) science and engineering based medical educational curriculum, and (ii) technologically oriented medical and surgical procedures. As such, this book can be usefully employed as a textbook for courses in (i) cardiovascular physiology in both the schools of engineering and medicine of universities, as well as (ii) cardiovascular engineering in biomedical engineering departments worldwide.

Computational Cardiovascular Mechanics provides a cohesive guide to creating mathematical models for the mechanics of diseased hearts to simulate the effects of current treatments for heart failure. Clearly organized in a two part structure, this volume discusses various areas of computational modeling of cardiovascular mechanics (finite element modeling of ventricular mechanics, fluid dynamics) in addition to a description an analysis of the current applications used (solid FE modeling, CFD). Edited by experts in the field, researchers involved with biomedical and mechanical engineering will find Computational Cardiovascular Mechanics a valuable reference.

Artificial Intelligence Medicine: Technical Basis and Clinical Applications presents a comprehensive overview of the field, ranging from its history and technical foundations, to specific clinical applications and finally to prospects. Artificial Intelligence (AI) is expanding across all domains at a breakneck speed. Medicine, with the availability of large multidimensional datasets, lends itself to strong potential advancement with the appropriate harnessing of AI. The integration of AI can occur throughout the continuum of medicine: from basic laboratory discovery to clinical application and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine. - Provides history and overview of artificial intelligence, as narrated by pioneers in the field - Discusses broad and deep background and updates on recent advances in both medicine and artificial intelligence that enabled the application of artificial intelligence - Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Addresses the mathematical and numerical modelling of the human cardiovascular system, from patient data to clinical applications.

Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient's heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model parameters from routine clinical data. Concepts are all illustrated through concrete clinical applications. - Presents recent advances in computational modeling of heart function and artificial intelligence technologies for subject-specific applications - Discusses AI-based technologies for robust anatomical modeling from medical images, data-driven reduction of multi-scale cardiac models, and estimations of physiological parameters from clinical data - Illustrates the technology through concrete clinical applications and discusses potential impacts and next steps needed for clinical translation