Machine Learning In Cardiovascular Medicine
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Machine Learning in Cardiovascular Medicine
Author | : Subhi J. Al'Aref,Gurpreet Singh,Lohendran Baskaran,Dimitri Metaxas |
Publsiher | : Academic Press |
Total Pages | : 456 |
Release | : 2020-11-20 |
Genre | : Science |
ISBN | : 9780128202746 |
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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
Deep Learning Applications in Medical Imaging
Author | : Saxena, Sanjay,Paul, Sudip |
Publsiher | : IGI Global |
Total Pages | : 274 |
Release | : 2020-10-16 |
Genre | : Medical |
ISBN | : 9781799850724 |
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Before the modern age of medicine, the chance of surviving a terminal disease such as cancer was minimal at best. After embracing the age of computer-aided medical analysis technologies, however, detecting and preventing individuals from contracting a variety of life-threatening diseases has led to a greater survival percentage and increased the development of algorithmic technologies in healthcare. Deep Learning Applications in Medical Imaging is a pivotal reference source that provides vital research on the application of generating pictorial depictions of the interior of a body for medical intervention and clinical analysis. While highlighting topics such as artificial neural networks, disease prediction, and healthcare analysis, this publication explores image acquisition and pattern recognition as well as the methods of treatment and care. This book is ideally designed for diagnosticians, medical imaging specialists, healthcare professionals, physicians, medical researchers, academicians, and students.
Deep Learning for Biomedical Applications
Author | : Utku Kose,Omer Deperlioglu,D. Jude Hemanth |
Publsiher | : CRC Press |
Total Pages | : 364 |
Release | : 2021-07-20 |
Genre | : Technology & Engineering |
ISBN | : 9781000406429 |
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This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics. The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.
Current and Future Role of Artificial Intelligence in Cardiac Imaging
Author | : Steffen Erhard Petersen,Karim Lekadir,Alistair A. Young,Tim Leiner |
Publsiher | : Frontiers Media SA |
Total Pages | : 138 |
Release | : 2020-10-09 |
Genre | : Medical |
ISBN | : 9782889660582 |
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This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Predicting Heart Failure
Author | : Kishor Kumar Sadasivuni,Hassen M. Ouakad,Somaya Al-Maadeed,Huseyin C. Yalcin,Issam Bait Bahadur |
Publsiher | : John Wiley & Sons |
Total Pages | : 356 |
Release | : 2022-04-05 |
Genre | : Medical |
ISBN | : 9781119813033 |
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PREDICTING HEART FAILURE Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods focuses on the mechanics and symptoms of heart failure and various approaches, including conventional and modern techniques to diagnose it. This book also provides a comprehensive but concise guide to all modern cardiological practice, emphasizing practical clinical management in many different contexts. Predicting Heart Failure supplies readers with trustworthy insights into all aspects of heart failure, including essential background information on clinical practice guidelines, in-depth, peer-reviewed articles, and broad coverage of this fast-moving field. Readers will also find: Discussion of the main characteristics of cardiovascular biosensors, along with their open issues for development and application Summary of the difficulties of wireless sensor communication and power transfer, and the utility of artificial intelligence in cardiology Coverage of data mining classification techniques, applied machine learning and advanced methods for estimating HF severity and diagnosing and predicting heart failure Discussion of the risks and issues associated with the remote monitoring system Assessment of the potential applications and future of implantable and wearable devices in heart failure prediction and detection Artificial intelligence in mobile monitoring technologies to provide clinicians with improved treatment options, ultimately easing access to healthcare by all patient populations. Providing the latest research data for the diagnosis and treatment of heart failure, Predicting Heart Failure: Invasive, Non-Invasive, Machine Learning and Artificial Intelligence Based Methods is an excellent resource for nurses, nurse practitioners, physician assistants, medical students, and general practitioners to gain a better understanding of bedside cardiology.
The Smart Cyber Ecosystem for Sustainable Development
Author | : Pardeep Kumar,Vishal Jain,Vasaki Ponnusamy |
Publsiher | : John Wiley & Sons |
Total Pages | : 484 |
Release | : 2021-09-08 |
Genre | : Technology & Engineering |
ISBN | : 9781119761662 |
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The Smart Cyber Ecosystem for Sustainable Development As the entire ecosystem is moving towards a sustainable goal, technology driven smart cyber system is the enabling factor to make this a success, and the current book documents how this can be attained. The cyber ecosystem consists of a huge number of different entities that work and interact with each other in a highly diversified manner. In this era, when the world is surrounded by many unseen challenges and when its population is increasing and resources are decreasing, scientists, researchers, academicians, industrialists, government agencies and other stakeholders are looking toward smart and intelligent cyber systems that can guarantee sustainable development for a better and healthier ecosystem. The main actors of this cyber ecosystem include the Internet of Things (IoT), artificial intelligence (AI), and the mechanisms providing cybersecurity. This book attempts to collect and publish innovative ideas, emerging trends, implementation experiences, and pertinent user cases for the purpose of serving mankind and societies with sustainable societal development. The 22 chapters of the book are divided into three sections: Section I deals with the Internet of Things, Section II focuses on artificial intelligence and especially its applications in healthcare, whereas Section III investigates the different cyber security mechanisms. Audience This book will attract researchers and graduate students working in the areas of artificial intelligence, blockchain, Internet of Things, information technology, as well as industrialists, practitioners, technology developers, entrepreneurs, and professionals who are interested in exploring, designing and implementing these technologies.
Coronary Microvascular Dysfunction
Author | : Filippo Crea,Gaetano A. Lanza,Paolo G. Camici |
Publsiher | : Springer Science & Business Media |
Total Pages | : 257 |
Release | : 2013-08-15 |
Genre | : Medical |
ISBN | : 9788847053670 |
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In the past two decades a number of studies have shown that abnormalities in the function and structure of coronary microcirculation can be detected in several cardiovascular diseases. On the basis of the clinical setting in which it occurs, coronary microvascular dysfunction (CMD) can be classified into four types: CMD in the absence of any other cardiac disease; CMD in myocardial diseases; CMD in obstructive epicardial coronary artery disease; and iatrogenic CMD. In some instances CMD represents an epiphenomenon, whereas in others it represents an important marker of risk or may contribute to the pathogenesis of myocardial ischemia, thus becoming a possible therapeutic target. This book provides an update on coronary physiology and a systematic assessment of microvascular abnormalities in cardiovascular diseases, in the hope that it will assist clinicians in prevention, detection and management of CMD in their everyday activity.
Systems Biology and Data Driven Machine Learning Based Models in Personalized Cardiovascular Medicine
Author | : Miguel Hueso,Joan Carles EscolĂ -Gil,Noemi Rotllan Vila,Alfredo Vellido |
Publsiher | : Frontiers Media SA |
Total Pages | : 225 |
Release | : 2023-11-15 |
Genre | : Medical |
ISBN | : 9782832539002 |
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