Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics

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  • Author : Pradeep N
  • Publisher : Academic Press
  • Pages : 372 pages
  • ISBN : 0128220449
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics

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 N and published by Academic Press which was released on 25 June 2021 with total page 372 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 the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to 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 Unique case study approach provides readers with insights for practical clinical implementation

Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics

Demystifying Big Data  Machine Learning  and Deep Learning for Healthcare Analytics
  • Author : Pradeep N,Sandeep Kautish,Sheng-Lung Peng
  • Publisher : Academic Press
  • Release : 25 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 the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision

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

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

Emerging Technologies in Healthcare

Emerging Technologies in Healthcare
  • Author : Matthew N. O. Sadiku,Rotimi A. K. Jaiyesimi,Joyce B. Idehen,Sarhan M. Musa
  • Publisher : AuthorHouse
  • Release : 05 October 2021
GET THIS BOOK Emerging Technologies in Healthcare

Health is regarded as one of the global challenges for mankind. Healthcare is a complex system that covers processes of diagnosis, treatment, and prevention of diseases. It constitutes a fundamental pillar of the modern society. Modern healthcare is technological healthcare. Technology is everywhere. This book focuses on twenty-one emerging technologies in the healthcare industry. An emerging technology is one that holds the promise of creating a new economic engine and is trans-industrial. Emerging technological trends are rapidly transforming businesses in

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
GET THIS BOOK Machine Learning with Health Care Perspective

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

Demystifying AI for the Enterprise

Demystifying AI for the Enterprise
  • Author : Prashant Natarajan,Bob Rogers,Edward Dixon,Jonas Christensen,Kirk Borne,Leland Wilkinson,Shantha Mohan
  • Publisher : CRC Press
  • Release : 31 December 2021
GET THIS BOOK Demystifying AI for the Enterprise

Artificial intelligence (AI) in its various forms –– machine learning, chatbots, robots, agents, etc. –– is increasingly being seen as a core component of enterprise business workflow and information management systems. The current promise and hype around AI are being driven by software vendors, academic research projects, and startups. However, we posit that the greatest promise and potential for AI lies in the enterprise with its applications touching all organizational facets. With increasing business process and workflow maturity, coupled with recent trends

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

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

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
  • Author : Adam Bohr,Kaveh Memarzadeh
  • Publisher : Academic Press
  • Release : 21 June 2020
GET THIS BOOK Artificial Intelligence in Healthcare

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its

Macular Surgery

Macular Surgery
  • Author : Andrew Chang,William F. Mieler,Masahito Ohji
  • Publisher : Springer Nature
  • Release : 20 January 2022
GET THIS BOOK Macular Surgery

"Recent technological advances in the diagnosis of macular disorders have enhanced our understanding of these diseases. At the same time, advances in small-gauge vitrectomy instrumentation and techniques have improved the safety and efficiency of surgery, allowing macular conditions that would have otherwise resulted in blindness to be treated effectively, preserving patients' sight. Macular surgery continues to evolve rapidly, thanks to exciting future technology trends. This book provides a detailed and up-to-date overview of the field. It begins with essential information

Advances in Surgery 2020

Advances in Surgery 2020
  • Author : John L. Cameron
  • Publisher : Elsevier Health Sciences
  • Release : 30 August 2020
GET THIS BOOK Advances in Surgery 2020

Each year, Advances in Surgery reviews the most current practices in general surgery. A distinguished editorial board, headed by Dr. John Cameron, identifies key areas of major progress and controversy and invites preeminent specialists to contribute original articles devoted to these topics. These insightful overviews in general surgery bring concepts to a clinical level and explore their everyday impact on patient care.

Research Anthology on Telemedicine Efficacy Adoption and Impact on Healthcare Delivery

Research Anthology on Telemedicine Efficacy  Adoption  and Impact on Healthcare Delivery
  • Author : Management Association, Information Resources
  • Publisher : IGI Global
  • Release : 15 January 2021
GET THIS BOOK Research Anthology on Telemedicine Efficacy Adoption and Impact on Healthcare Delivery

Telemedicine, which involves electronic communications and software, provides the same clinical services to patients without the requirement of an in-person visit. Essentially, this is considered remote healthcare. Though telemedicine is not a new practice, it has become an increasingly popular form of healthcare delivery due to current events, including the COVID-19 pandemic. Not only are visits being moved onto virtual platforms, but additional materials and correspondence can remain in the digital sphere. Virtual lab results, digital imaging, medical diagnosis, and

Impacts of Information Technology on Patient Care and Empowerment

Impacts of Information Technology on Patient Care and Empowerment
  • Author : McHaney, Roger W.,Reychev, Iris,Azuri, Joseph,McHaney, Mark E.,Moshonov, Rami
  • Publisher : IGI Global
  • Release : 20 September 2019
GET THIS BOOK Impacts of Information Technology on Patient Care and Empowerment

Modern technology has impacted healthcare and interactions between patients and healthcare providers through a variety of means including the internet, social media, mobile devices, and the internet of things. These new technologies have empowered, frustrated, educated, and confused patients by making educational materials more widely available and allowing patients to monitor their own vital signs and self-diagnose. Further analysis of these and future technologies is needed in order to provide new approaches to empowerment, reduce mistakes, and improve overall healthcare.

Demystifying China s Innovation Machine

Demystifying China s Innovation Machine
  • Author : Marina Zhang,Mark Dodgson,David Gann
  • Publisher : Oxford University Press
  • Release : 08 December 2021
GET THIS BOOK Demystifying China s Innovation Machine

China's extraordinary economic development is explained in large part by the way it innovates. Contrary to widely held views, China's innovation machine is not created and controlled by an all-powerful government. Instead, it is a complex, interdependent system composed of various elements, involving bottom-up innovation driven by innovators and entrepreneurs and highly pragmatic and adaptive top-down policy. Using case studies of leading firms and industries, along with statistics and policy analysis, this book argues that China's innovation machine is similar

Demystifying Digital Transformation

Demystifying Digital Transformation
  • Author : Nishith Sharan,Tushar Khosla
  • Publisher : Notion Press
  • Release : 03 January 2019
GET THIS BOOK Demystifying Digital Transformation

Digital transformation is inevitable, for organisations who seek to remain relevant in the future. The objective of any digital transformation is to innovatively apply the technology stack to reinvent the organisation and the way in which it will engage with the customer to deliver value to them. Given that each organisation has a unique DNA with distinctive aspirations, the digital journey need to be individually crafted with clear purpose, technology choices, and implementation specifics. Leaders will be called upon to