Machine Learning in Cardiovascular Medicine

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

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  • Author : Subhi J. Al'Aref
  • Publisher : Academic Press
  • Pages : 454 pages
  • ISBN : 0128202742
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKMachine Learning in Cardiovascular Medicine

Machine Learning in Cardiovascular Medicine

Machine Learning in Cardiovascular Medicine
  • Author : Subhi J. Al'Aref,Gurpreet Singh,Lohendran Baskaran,Dimitri Metaxas
  • Publisher : Academic Press
  • Release : 20 November 2020
GET THIS BOOKMachine Learning in Cardiovascular Medicine

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

Machine Learning in Cardiovascular Medicine

Machine Learning in Cardiovascular Medicine
  • Author : Subhi J. Al'Aref, M.D.,Gurpreet Singh,Lohendran Baskaran,Dimitri Metaxas
  • Publisher : Academic Press
  • Release : 11 December 2020
GET THIS BOOKMachine Learning in Cardiovascular Medicine

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

Applications of Machine Learning

Applications of Machine Learning
  • Author : Prashant Johri,Jitendra Kumar Verma,Sudip Paul
  • Publisher : Springer Nature
  • Release : 04 May 2020
GET THIS BOOKApplications of Machine Learning

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.

Deep Learning for Biomedical Applications

Deep Learning for Biomedical Applications
  • Author : Utku Kose,Omer Deperlioglu,D. Jude Hemanth
  • Publisher : CRC Press
  • Release : 20 July 2021
GET THIS BOOKDeep Learning for Biomedical Applications

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,

Deep Learning Applications in Medical Imaging

Deep Learning Applications in Medical Imaging
  • Author : Sanjay Saxena,Sudip Paul
  • Publisher : Unknown Publisher
  • Release : 01 August 2020
GET THIS BOOKDeep Learning Applications in Medical Imaging

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

CT of the Heart

CT of the Heart
  • Author : U. Joseph Schoepf
  • Publisher : Humana Press
  • Release : 01 April 2019
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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

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
  • Author : Lei Xing,Maryellen L. Giger,James K. Min
  • Publisher : Academic Press
  • Release : 03 September 2020
GET THIS BOOKArtificial Intelligence in Medicine

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

Handbook of Research on Applied Intelligence for Health and Clinical Informatics

Handbook of Research on Applied Intelligence for Health and Clinical Informatics
  • Author : Thakare, Anuradha Dheeraj,Wagh, Sanjeev J.,Bhende, Manisha Sunil,Anter, Ahmed M.,Gao, Xiao-Zhi
  • Publisher : IGI Global
  • Release : 22 October 2021
GET THIS BOOKHandbook of Research on Applied Intelligence for Health and Clinical Informatics

Currently, informatics within the field of public health is a developing and growing industry. Clinical informatics are used in direct patient care by supplying medical practitioners with information that can be used to develop a care plan. Intelligent applications in clinical informatics facilitates with the technology-based solutions to analyze data or medical images and help clinicians to retrieve that information. Decision models aid with making complex decisions especially in uncertain situations. The Handbook of Research on Applied Intelligence for Health

Machine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare
  • Author : Krishna Kant Singh,Mohamed Elhoseny,Akansha Singh,Ahmed A. Elngar
  • Publisher : Academic Press
  • Release : 26 April 2021
GET THIS BOOKMachine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and

Machine Learning and Its Applications

Machine Learning and Its Applications
  • Author : Georgios Paliouras,Vangelis Karkaletsis,Constantine D. Spyropoulos
  • Publisher : Springer
  • Release : 29 June 2003
GET THIS BOOKMachine Learning and Its Applications

In recent years machine learning has made its way from artificial intelligence into areas of administration, commerce, and industry. Data mining is perhaps the most widely known demonstration of this migration, complemented by less publicized applications of machine learning like adaptive systems in industry, financial prediction, medical diagnosis and the construction of user profiles for Web browsers. This book presents the capabilities of machine learning methods and ideas on how these methods could be used to solve real-world problems. The

Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems

Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems
  • Author : Om Prakash Jena,Bharat Bhushan,Nitin Rakesh,Parma Nand Astya,Yousef Farhaoui
  • Publisher : Emerging Trends in Biomedical Technologies and Health informatics
  • Release : 26 May 2022
GET THIS BOOKMachine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems

This book describes the fundamental concepts of machine learning and deep learning techniques in a healthcare system. The aim of this book is to describe how deep learning methods are used to insure high quality data processing, medical image and signal analysis, and improved healthcare application.

Deep Learning in Healthcare

Deep Learning in Healthcare
  • Author : Yen-Wei Chen,Lakhmi C. Jain
  • Publisher : Springer Nature
  • Release : 18 November 2019
GET THIS BOOKDeep Learning in Healthcare

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,

Image Processing for Automated Diagnosis of Cardiac Diseases

Image Processing for Automated Diagnosis of Cardiac Diseases
  • Author : Kalpana Chauhan,Rajeev Kumar Chauhan
  • Publisher : Academic Press
  • Release : 13 July 2021
GET THIS BOOKImage Processing for Automated Diagnosis of Cardiac Diseases

Image Processing for Automated Diagnosis of Cardiac Diseases highlights current and emerging technologies for the automated diagnosis of cardiac diseases. It presents concepts and practical algorithms, including techniques for the automated diagnosis of organs in motion using image processing. This book is suitable for biomedical engineering researchers, engineers and scientists in research and development, and clinicians who want to learn more about and develop advanced concepts in image processing to overcome the challenges of automated diagnosis of heart disease. Includes

Machine Learning in Medicine - a Complete Overview

Machine Learning in Medicine - a Complete Overview
  • Author : Ton J. Cleophas,Aeilko H. Zwinderman
  • Publisher : Springer
  • Release : 27 March 2015
GET THIS BOOKMachine Learning in Medicine - a Complete Overview

The current book is the first publication of a complete overview of machine learning methodologies for the medical and health sector. It was written as a training companion and as a must-read, not only for physicians and students, but also for any one involved in the process and progress of health and health care. In eighty chapters eighty different machine learning methodologies are reviewed, in combination with data examples for self-assessment. Each chapter can be studied without the need to

Handbook of Robotic and Image-Guided Surgery

Handbook of Robotic and Image-Guided Surgery
  • Author : Mohammad Abedin-Nasab
  • Publisher : Elsevier
  • Release : 25 September 2019
GET THIS BOOKHandbook of Robotic and Image-Guided Surgery

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