Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics

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  • Author : Pradeep Nijalingappa
  • Publisher : Academic Press
  • Pages : 332 pages
  • ISBN : 0128220449
  • Rating : /5 from reviews
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Download or Read online Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics full in PDF, ePub and kindle. this book written by Pradeep Nijalingappa and published by Academic Press which was released on 01 June 2021 with total page 332 pages. We cannot guarantee that Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents how these emerging areas are changing the world of data utilization, especially in clinical healthcare. Various techniques, methodologies and algorithms are presented in a structured manner to assist physicians in the precision care of patients and help biomedical engineers and computers scientists understand the impact of these techniques on healthcare analytics. Sections cover Big Data aspects, i.e., healthcare Decision Support Systems and Analytics related topics, focus on current frameworks and applications of Deep Learning and Machine Learning, and provide an outlook on future directions. The entire book takes a case study approach, providing a wealth of real-world case studies that act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers and clinicians. Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers and clinicians to understand and develop healthcare analytics using advanced tools and technologies Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables and graphs with algorithms and computational methods for developing new applications in healthcare informatics Presents a unique case study approach that provides readers with insights for practical clinical implementations

Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics

Demystifying Big Data  Machine Learning  and Deep Learning for Healthcare Analytics
  • Author : Pradeep Nijalingappa,Sandeep Kautish,Sheng Lung Peng
  • Publisher : Academic Press
  • Release : 01 June 2021
GET THIS BOOK Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents how these emerging areas are changing the world of data utilization, especially in clinical healthcare. Various techniques, methodologies and algorithms are presented in a structured manner to assist physicians in the precision care of patients and help biomedical engineers and computers scientists understand the impact of these techniques on healthcare analytics. Sections cover Big Data aspects, i.e., healthcare Decision Support Systems and Analytics related topics, focus on

Demystifying Big Data and Machine Learning for Healthcare

Demystifying Big Data and Machine Learning for Healthcare
  • Author : Prashant Natarajan,John C. Frenzel,Detlev H. Smaltz
  • Publisher : CRC Press
  • Release : 15 February 2017
GET THIS BOOK Demystifying Big Data and Machine Learning for Healthcare

Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the

Machine Learning with Health Care Perspective

Machine Learning with Health Care Perspective
  • Author : Vishal Jain,Jyotir Moy Chatterjee
  • Publisher : Springer Nature
  • Release : 09 March 2020
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This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how

Intelligence Based Medicine

Intelligence Based Medicine
  • Author : Anthony C. Chang
  • Publisher : Academic Press
  • Release : 27 June 2020
GET THIS BOOK Intelligence Based Medicine

Intelligence-Based Medicine: Data Science, Artificial Intelligence, and Human Cognition in Clinical Medicine and Healthcare provides a multidisciplinary and comprehensive survey of artificial intelligence concepts and methodologies with real life applications in healthcare and medicine. Authored by a senior physician-data scientist, the book presents an intellectual and academic interface between the medical and the data science domains that is symmetric and balanced. The content consists of basic concepts of artificial intelligence and its real-life applications in a myriad of medical areas

Information and Communication Technologies for Development Evaluation

Information and Communication Technologies for Development Evaluation
  • Author : Oscar A. García,Prashanth Kotturi
  • Publisher : Routledge
  • Release : 09 July 2019
GET THIS BOOK Information and Communication Technologies for Development Evaluation

Written by a team of expert practitioners at the Independent Office of Evaluation of International Fund for Agricultural Development (IFAD), this book gives an insight into the implications of new and emerging technologies in development evaluation. Growing technologies such as big data analytics, machine learning and remote sensing present new opportunities for development practitioners and development evaluators, particularly when measuring indicators of the Sustainable Development Goals. The volume provides an overview of information and communication technologies (ICTs) in the context

A Global Approach to Data Value Maximization

A Global Approach to Data Value Maximization
  • Author : Paolo Dell’Aversana
  • Publisher : Cambridge Scholars Publishing
  • Release : 17 April 2019
GET THIS BOOK A Global Approach to Data Value Maximization

This book presents a systematic discussion about methods and techniques used to extract the maximum informative value from complex data sets. A multitude of approaches and techniques can be applied for that purpose, including data fusion and model integration, multimodal data analysis in different physical domains, audio-video display of data through techniques of “sonification”, multimedia machine learning, and hybrid methods of data analysis. The book begins with the domain of geosciences, before moving on to other scientific areas, like diagnostic

Generative Adversarial Networks for Image to Image Translation

Generative Adversarial Networks for Image to Image Translation
  • Author : Arun Solanki,Anand Nayyar,Mohd Naved
  • Publisher : Academic Press
  • Release : 01 June 2021
GET THIS BOOK Generative Adversarial Networks for Image to Image Translation

Generative Adversarial Networks (GAN) have started a revolution in Deep Learning, and today GAN is one of the most researched topics in Artificial Intelligence. Generative Adversarial Networks for Image-to-Image Translation provides a comprehensive overview of the GAN (Generative Adversarial Network) concept starting from the original GAN network to various GAN-based systems such as Deep Convolutional GANs (DCGANs), Conditional GANs (cGANs), StackGAN, Wasserstein GANs (WGAN), cyclical GANs, and many more. The book also provides readers with detailed real-world applications and common

Handbook of Research on Emerging Trends and Applications of Machine Learning

Handbook of Research on Emerging Trends and Applications of Machine Learning
  • Author : Solanki, Arun,Kumar, Sandeep,Nayyar, Anand
  • Publisher : IGI Global
  • Release : 13 December 2019
GET THIS BOOK Handbook of Research on Emerging Trends and Applications of Machine Learning

As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world.

The Digital Twin Paradigm for Smarter Systems and Environments the Industry Use Cases

The Digital Twin Paradigm for Smarter Systems and Environments  the Industry Use Cases
  • Author : Preetha Evangeline
  • Publisher : Academic Press
  • Release : 01 February 2020
GET THIS BOOK The Digital Twin Paradigm for Smarter Systems and Environments the Industry Use Cases

The Digital Twin Paradigm for Smarter Systems and Environments: The Industry Use Cases, Volume 117, the latest volume in the Advances in Computers series, presents detailed coverage of new advancements in computer hardware, software, theory, design and applications. Chapters vividly illustrate how the emerging discipline of digital twin is strategically contributing to various digital transformation initiatives. Specific chapters cover Demystifying the Digital Twin Paradigm, Digital Twin Technology for "Smarter Manufacturing", The Fog Computing/ Edge Computing to leverage Digital Twin, The industry