Machine Learning in Cardiovascular Medicine Book

Machine Learning in Cardiovascular Medicine

  • Author : Subhi J. Al'Aref
  • Publisher : Academic Press
  • Release Date : 2020-11-20
  • Genre: Medical
  • Pages : 454
  • ISBN 10 : 9780128202746

Machine Learning in Cardiovascular Medicine Excerpt :

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 Book

Deep Learning Applications in Medical Imaging

  • Author : Saxena, Sanjay
  • Publisher : IGI Global
  • Release Date : 2020-10-16
  • Genre: Medical
  • Pages : 274
  • ISBN 10 : 9781799850724

Deep Learning Applications in Medical Imaging Excerpt :

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 Book

Deep Learning for Biomedical Applications

  • Author : Utku Kose
  • Publisher : CRC Press
  • Release Date : 2021-07-20
  • Genre: Technology & Engineering
  • Pages : 364
  • ISBN 10 : 9781000406429

Deep Learning for Biomedical Applications Excerpt :

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.

Precision Medicine in Cardiovascular Disease Prevention Book

Precision Medicine in Cardiovascular Disease Prevention

  • Author : Seth S. Martin
  • Publisher : Springer Nature
  • Release Date : 2021-07-07
  • Genre: Medical
  • Pages : 194
  • ISBN 10 : 9783030750558

Precision Medicine in Cardiovascular Disease Prevention Excerpt :

This book contains the current knowledge and potential future developments of precision medicine techniques including artificial intelligence, big data, mobile health, digital health and genetic medicine in the prevention of cardiovascular disease. It reviews the presently used advanced precision medicine techniques and fundamental principles that continue to act as guiding forces for many medical professionals in applying precision and preventative medical techniques in their day-to-day practices. Precision Medicine in Cardiovascular Disease Prevention describes current knowledge and potential future developments in this rapidly expanding field. It therefore provides a valuable resource for all practicing and trainee cardiologists looking to develop their knowledge and integrate precision medicine techniques into their practices.

Fundamentals and Methods of Machine and Deep Learning Book

Fundamentals and Methods of Machine and Deep Learning

  • Author : Pradeep Singh
  • Publisher : John Wiley & Sons
  • Release Date : 2022-02-01
  • Genre: Computers
  • Pages : 480
  • ISBN 10 : 9781119821885

Fundamentals and Methods of Machine and Deep Learning Excerpt :

FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING The book provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications. Over the past two decades, the field of machine learning and its subfield deep learning have played a main role in software applications development. Also, in recent research studies, they are regarded as one of the disruptive technologies that will transform our future life, business, and the global economy. The recent explosion of digital data in a wide variety of domains, including science, engineering, Internet of Things, biomedical, healthcare, and many business sectors, has declared the era of big data, which cannot be analysed by classical statistics but by the more modern, robust machine learning and deep learning techniques. Since machine learning learns from data rather than by programming hard-coded decision rules, an attempt is being made to use machine learning to make computers that are able to solve problems like human experts in the field. The goal of this book is to present a??practical approach by explaining the concepts of machine learning and deep learning algorithms with applications. Supervised machine learning algorithms, ensemble machine learning algorithms, feature selection, deep learning techniques, and their applications are discussed. Also included in the eighteen chapters is unique information which provides a clear understanding of concepts by using algorithms and case studies illustrated with applications of machine learning and deep learning in different domains, including disease prediction, software defect prediction, online television analysis, medical image processing, etc. Each of the chapters briefly described below provides both a chosen approach and its implementation. Audience Researchers and engineers in artificial intelligence, computer scientists as well as software develo

Applications of Machine Learning Book
Score: 1
From 1 Ratings

Applications of Machine Learning

  • Author : Prashant Johri
  • Publisher : Springer Nature
  • Release Date : 2020-05-04
  • Genre: Technology & Engineering
  • Pages : 394
  • ISBN 10 : 9789811533570

Applications of Machine Learning Excerpt :

This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.

Current and Future Role of Artificial Intelligence in Cardiac Imaging Book

Current and Future Role of Artificial Intelligence in Cardiac Imaging

  • Author : Steffen Erhard Petersen
  • Publisher : Frontiers Media SA
  • Release Date : 2020-10-09
  • Genre: Medical
  • Pages : 138
  • ISBN 10 : 9782889660582

Current and Future Role of Artificial Intelligence in Cardiac Imaging Excerpt :

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:

CT of the Heart Book

CT of the Heart

  • Author : U. Joseph Schoepf
  • Publisher : Humana Press
  • Release Date : 2019-04-01
  • Genre: Medical
  • Pages : 931
  • ISBN 10 : 9781603272377

CT of the Heart Excerpt :

This book is a comprehensive and richly-illustrated guide to cardiac CT, its current state, applications, and future directions. While the first edition of this text focused on what was then a novel instrument looking for application, this edition comes at a time where a wealth of guideline-driven, robust, and beneficial clinical applications have evolved that are enabled by an enormous and ever growing field of technology. Accordingly, the focus of the text has shifted from a technology-centric to a more patient-centric appraisal. While the specifications and capabilities of the CT system itself remain front and center as the basis for diagnostic success, much of the benefit derived from cardiac CT today comes from avant-garde technologies enabling enhanced visualization, quantitative imaging, and functional assessment, along with exciting deep learning, and artificial intelligence applications. Cardiac CT is no longer a mere tool for non-invasive coronary artery stenosis detection in the chest pain diagnostic algorithms; cardiac CT has proven its value for uses as diverse as personalized cardiovascular risk stratification, prediction, and management, diagnosing lesion-specific ischemia, guiding minimally invasive structural heart disease therapy, and planning cardiovascular surgery, among many others. This second edition is an authoritative guide and reference for both novices and experts in the medical imaging sciences who have an interest in cardiac CT.

Coronary Microvascular Dysfunction Book

Coronary Microvascular Dysfunction

  • Author : Filippo Crea
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-08-15
  • Genre: Medical
  • Pages : 257
  • ISBN 10 : 9788847053670

Coronary Microvascular Dysfunction Excerpt :

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.

Artificial Intelligence in Medical Imaging Book

Artificial Intelligence in Medical Imaging

  • Author : Erik R. Ranschaert
  • Publisher : Springer
  • Release Date : 2019-01-29
  • Genre: Medical
  • Pages : 373
  • ISBN 10 : 9783319948782

Artificial Intelligence in Medical Imaging Excerpt :

This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning Book

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning

  • Author : Rani, Geeta
  • Publisher : IGI Global
  • Release Date : 2020-10-16
  • Genre: Medical
  • Pages : 586
  • ISBN 10 : 9781799827436

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning Excerpt :

By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

Adult Congenital Heart Disease Book

Adult Congenital Heart Disease

  • Author : Michael A. Gatzoulis
  • Publisher : John Wiley & Sons
  • Release Date : 2008-04-15
  • Genre: Medical
  • Pages : 288
  • ISBN 10 : 9781405144537

Adult Congenital Heart Disease Excerpt :

Congenital heart disease with its worldwide incidence of 1% is themost common inborn defect. Increasingly, patients are living intoadulthood, with ongoing congenital heart and other medical needs.Sadly, only a small minority have specialist follow-up. However,all patients see their family doctor and may also seek advice fromother health professionals. This practical guide with its straightforward a,b,c approach iswritten for those professionals. Special features of this book: • Introduces the principles of congenital heart diseaseand tells you whom and when to refer for specialist care • Discusses common congenital heart lesions in a practical,easy-to-follow way, with an emphasis on diagnosis and managementissues • Includes an extensive chapter on 'Pregnancy andContraception' (by Philip J. Steer), essential both for familyplanning and for managing safely the pregnant woman with congenitalheart disease • Includes chapters on non-cardiac surgery and lifestyleissues such as work, insurability, travel and driving • Provides invaluable information on dealing with commonemergencies; what to do and what not to do With a wealth of illustrations (including diagrams, EKGs, CXRs,Echos and cardiac MRIs) and with key point tables, this is anessential guide for all health care professionals managing patientswith adult congenital heart disease.

Interpretable Machine Learning Book
Score: 4.5
From 2 Ratings

Interpretable Machine Learning

  • Author : Christoph Molnar
  • Publisher :
  • Release Date : 2020
  • Genre: Artificial intelligence
  • Pages : 320
  • ISBN 10 : 9780244768522

Interpretable Machine Learning Excerpt :

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Handbook of Robotic and Image Guided Surgery Book

Handbook of Robotic and Image Guided Surgery

  • Author : Mohammad Abedin-Nasab
  • Publisher : Elsevier
  • Release Date : 2019-09-25
  • Genre: Science
  • Pages : 752
  • ISBN 10 : 9780128142462

Handbook of Robotic and Image Guided Surgery Excerpt :

Handbook of Robotic and Image-Guided Surgery provides state-of-the-art systems and methods for robotic and computer-assisted surgeries. In this masterpiece, contributions of 169 researchers from 19 countries have been gathered to provide 38 chapters. This handbook is 744 pages, includes 659 figures and 61 videos. It also provides basic medical knowledge for engineers and basic engineering principles for surgeons. A key strength of this text is the fusion of engineering, radiology, and surgical principles into one book. A thorough and in-depth handbook on surgical robotics and image-guided surgery which includes both fundamentals and advances in the field A comprehensive reference on robot-assisted laparoscopic, orthopedic, and head-and-neck surgeries Chapters are contributed by worldwide experts from both engineering and surgical backgrounds

Deep Learning in Healthcare Book

Deep Learning in Healthcare

  • Author : Yen-Wei Chen
  • Publisher : Springer Nature
  • Release Date : 2019-11-18
  • Genre: Technology & Engineering
  • Pages : 218
  • ISBN 10 : 9783030326067

Deep Learning in Healthcare Excerpt :

This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data. Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.