Cardiovascular Computing Methodologies And Clinical Applications

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.

Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. Provides an overview of machine learning, both for a clinical and engineering audience Summarize recent advances in both cardiovascular medicine and artificial intelligence Discusses the advantages of using machine learning for outcomes research and image processing Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Personalized Health Systems for Cardiovascular Disease is intended for researchers, developers, and designers in the field of p-health, with a specific focus on management of cardiovascular diseases. Biomedical engineers will benefit from coverage of sensors, data transmission, signal processing, data analysis, home and mobile applications, standards, and all other subject matters developed in this book in order to provide an integrated view of the different and multidisciplinary problems related to p-health systems. However, many chapters will also be interesting to physicians and other professionals who operate in the health domain. Students, MS and PhD level, mainly in technical universities, but also in medical schools, will find in this book a complete view of the manifold aspects of p-health, including technical problems related to sensors and software, to automatic evaluation and correct interpretation of the data, and also some legal and regulatory aspects. This book mainly focuses on the development of technology used by people and patients in the management of their own health. New wearable and implantable devices allow a continuous monitoring of chronic patients, with a direct involvement of clinical centers and physicians. Also, healthy people are more and more interested in keeping their own wellness under control, by adopting healthy lifestyles and identifying any early sign of risk. This is leading to personalized solutions via systems which are tailored to a specific patient/person and her/ his needs. However, many problems are still open when it comes to p-health systems. Which sensors and parameters should be used? Which software and analysis? When and how? How do you design an effective management plan for chronic pathologies such as cardiovascular diseases? What is useful feedback for the patient or for the clinician? And finally, what are the limits of this approach? What is the view of physicians? The purpose of this book is to provide, from a technical point of view, a complete description of most of the elements which are part of such systems, including the sensors and the hardware, the signal processing and data management procedures, the classification and stratification models, the standards and the regulations, focusing on the state of the art and identifying the new directions for innovative solutions. In this book, readers will find the fundamental elements that must be taken into account when developing devices and systems in the field of p-health. Provides an integrated approach to design and development of p-health systems which involves sensors, analysis software, user interfaces, data modeling, and interpretation. Covers standards and regulations on data privacy and security, plus safe design of devices. Supported by case studies discussing development of actual solutions in the biomedical engineering field.

Third edition of International Conference on Intelligent Computing and Optimization and as a premium fruit, this book, pursue to gather research leaders, experts and scientists on Intelligent Computing and Optimization to share knowledge, experience and current research achievements. Conference and book provide a unique opportunity for the global community to interact and share novel research results, explorations and innovations among colleagues and friends. This book is published by SPRINGER, Advances in Intelligent Systems and Computing. Ca. 100 authors submitted full papers to ICO’2020. That global representation demonstrates the growing interest of the research community here. The book covers innovative and creative research on sustainability, smart cities, meta-heuristics optimization, cyber-security, block chain, big data analytics, IoTs, renewable energy, artificial intelligence, Industry 4.0, modeling and simulation. We editors thank all authors and reviewers for their important service. Best high-quality papers have been selected by the International PC for our premium series with SPRINGER.

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

This book provides insights of World Conference on Smart Trends in Systems, Security and Sustainability (WS4 2021) which is divided into different sections such as Smart IT Infrastructure for Sustainable Society; Smart Management prospective for Sustainable Society; Smart Secure Systems for Next Generation Technologies; Smart Trends for Computational Graphics and Image Modeling; and Smart Trends for Biomedical and Health Informatics. The proceedings is presented in two volumes. The book is helpful for active researchers and practitioners in the field.