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Big Data Analytics in Healthcare

  • Book
  • © 2020

Overview

Editors:
  1. Anand J. Kulkarni

    1. Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, India

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  2. Patrick Siarry

    1. Université Paris-Est Créteil Val de Marne, Créteil, France

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  3. Pramod Kumar Singh

    1. ABV-Indian Institute of Information Technology and Management Gwalior, Gwalior, India

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  4. Ajith Abraham

    1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, USA

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  5. Mengjie Zhang

    1. School of Engineering and Computer Science, Victoria University of Wellington, Kelburn, New Zealand

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  6. Albert Zomaya

    1. School of Computer Science, University of Sydney, Sydney, Australia

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  7. Fazle Baki

    1. Odette School of Business, University of Windsor, Windsor, Canada

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  • Presents novel as well as modified heuristics and metaheuristics along with its validation by solving complex big data problems associated with healthcare
  • Discusses a multifaceted and state-of-the-art literature survey associated with the healthcare data, their modalities, complexities and methodologies along with a complete mathematical formulation
  • Provides recent research on big data analytics in healthcare

Part of the book series: Studies in Big Data (SBD, volume 66)

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About this book

This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers, scientists, and students studying/involved in the development of big data tools in the areas of healthcare and medicine. It also features a multifaceted and state-of-the-art literature review on healthcare data, its modalities, complexities, and methodologies, along with mathematical formulations.

The book is divided into two main sections, the first of which discusses the challenges and opportunities associated with the implementation of big data in the healthcare sector. In turn, the second addresses the mathematical modeling of healthcare problems, as well as current and potential future big data applications and platforms.

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Keywords

Table of contents (9 chapters)

  1. Front Matter

    Pages i-xi
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  2. Challenges, Opportunities, Platforms and Tools of Big Data in Healthcare

    1. Front Matter

      Pages 1-1
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    2. Big Data Analytics and Its Benefits in Healthcare

      • Yogesh Kumar, Kanika Sood, Surabhi Kaul, Richa Vasuja
      Pages 3-21

    3. Elements of Healthcare Big Data Analytics

      • Nishita Mehta, Anil Pandit, Meenal Kulkarni
      Pages 23-43

    4. Big Data in Supply Chain Management and Medicinal Domain

      • Aniket Nargundkar, Anand J. Kulkarni
      Pages 45-54

    5. A Review of Big Data and Its Applications in Healthcare and Public Sector

      • Apoorva Shastri, Mihir Deshpande
      Pages 55-66

    6. Big Data in Healthcare: Technical Challenges and Opportunities

      • Ganesh M. Kakandikar, Vilas M. Nandedkar
      Pages 67-81

    7. Innovative mHealth Solution for Reliable Patient Data Empowering Rural Healthcare in Developing Countries

      • Jay Rajasekera, Aditi Vivek Mishal, Yoshie Mori
      Pages 83-104

  3. Mathematical Modeling and Solutions, Big Data Applications, and Platforms

    1. Front Matter

      Pages 105-105
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    2. Hospital Surgery Scheduling Under Uncertainty Using Multiobjective Evolutionary Algorithms

      • Kazi Shah Nawaz Ripon, Jacob Henrik Nyman
      Pages 107-142

    3. Big Data in Electroencephalography Analysis

      • Dhanalekshmi P. Yedurkar, Shilpa P. Metkar
      Pages 143-153

    4. Big Data Analytics in Healthcare Using Spreadsheets

      • Samaya Pillai Iyengar, Haridas Acharya, Manik Kadam
      Pages 155-187
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Editors and Affiliations

  • Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, India

    Anand J. Kulkarni

  • Université Paris-Est Créteil Val de Marne, Créteil, France

    Patrick Siarry

  • ABV-Indian Institute of Information Technology and Management Gwalior, Gwalior, India

    Pramod Kumar Singh

  • Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, USA

    Ajith Abraham

  • School of Engineering and Computer Science, Victoria University of Wellington, Kelburn, New Zealand

    Mengjie Zhang

  • School of Computer Science, University of Sydney, Sydney, Australia

    Albert Zomaya

  • Odette School of Business, University of Windsor, Windsor, Canada

    Fazle Baki

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