Big Data Analytics for Intelligent Healthcare Management

Big Data Analytics for Intelligent Healthcare Management

1st Edition - April 13, 2019

Write a review

  • Editors: Nilanjan Dey, Himansu Das, Bighnaraj Naik, H S Behera
  • eBook ISBN: 9780128181478
  • Paperback ISBN: 9780128181461

Purchase options

Purchase options
DRM-free (Mobi, PDF, EPub)
Available
Sales tax will be calculated at check-out

Institutional Subscription

Free Global Shipping
No minimum order

Description

Big Data Analytics for Intelligent Healthcare Management covers both the theory and application of hardware platforms and architectures, the development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of big data in healthcare and clinical research. The book provides the latest research findings on the use of big data analytics with statistical and machine learning techniques that analyze huge amounts of real-time healthcare data.

Key Features

  • Examines the methodology and requirements for development of big data architecture, big data modeling, big data as a service, big data analytics, and more
  • Discusses big data applications for intelligent healthcare management, such as revenue management and pricing, predictive analytics/forecasting, big data integration for medical data, algorithms and techniques, etc.
  • Covers the development of big data tools, such as data, web and text mining, data mining, optimization, machine learning, cloud in big data with Hadoop, big data in IoT, and more

Readership

Biomedical engineers, researchers in data analytics, Big Data, health care management and intelligent systems

Table of Contents

  • 1. Bio-Inspired Algorithms for Big Data Analytics: A Survey, Taxonomy, and Open Challenges
    2. Big Data Analytics Challenges and Solutions
    3. Big Data Analytics in Healthcare: A Critical Analysis
    4. Transfer Learning and Supervised Classifier Based Prediction Model for Breast Cancer
    5. Chronic TTH Analysis by EMG and GSR Biofeedback on Various Modes and Various Medical Symptoms Using IoT
    6. Multilevel Classification Framework of fMRI Data: A Big Data Approach
    7. Smart Healthcare: An Approach for Ubiquitous Healthcare Management Using IOT
    8. Blockchain in Healthcare: Challenges and Solutions
    9. Intelligence-Based Health Recommendation System Using Big Data Analytics
    10. Computational Biology Approach in Management of Big Data of Healthcare Sector
    11. Kidney-Inspired Algorithm and Fuzzy Clustering for Biomedical Data Analysis

Product details

  • No. of pages: 312
  • Language: English
  • Copyright: © Academic Press 2019
  • Published: April 13, 2019
  • Imprint: Academic Press
  • eBook ISBN: 9780128181478
  • Paperback ISBN: 9780128181461

About the Editors

Nilanjan Dey

Nilanjan Dey is an Associate Professor in the Department of Computer Science and Engineering, JIS University, Kolkata, India. He is a visiting fellow of the University of Reading, UK, and also holds the position of Adjunct Professor at Ton Duc Thang University, Ho Chi Minh City, Vietnam. Previously, he held the honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012–2015). He got his PhD from Jadavpur University in 2015. He is the Editor-in-Chief of the International Journal of Ambient Computing and Intelligence, IGI Global, USA. He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing (Springer Nature), Data-Intensive Research (Springer Nature), Advances in Ubiquitous Sensing Applications for Healthcare (Elsevier). He is an associate editor of IET Image Processing (Wiley) and an editorial board member of Complex & Intelligent Systems (Springer Nature), Applied Soft Computing (Elsevier), and more. He has written 110 books and over 300 other publications in the areas of medical imaging, machine learning, computer aided diagnosis, data mining, etc. His works have been cited over 15,000 times. He is India’s Ambassador to the International Federation for Information Processing—Young ICT Group and a senior member of IEEE.

Affiliations and Expertise

Department of Computer Science & Engineering, Maulana Abul Kalam Azad JIS University, Agarpara, Kolkata, India.

Himansu Das

Himansu Das is working as an as Assistant Professor in the School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India. He has received his B. Tech and M. Tech degree from Biju Pattnaik University of Technology (BPUT), Odisha, India. He has published several research papers in various international journals and conferences. He has also edited several books of international repute. He is associated with different international bodies as Editorial/Reviewer board member of various journals and conferences. He is a proficient in the field of Computer Science Engineering and served as an organizing chair, publicity chair and act as member of program committees of many national and international conferences. He is also associated with various educational and research societies like IACSIT, ISTE, UACEE, CSI, IET, IAENG, ISCA etc., His research interest includes Grid Computing, Cloud Computing, and Machine Learning. He has also 10 years of teaching and research experience in different engineering colleges.

Affiliations and Expertise

Assistant Professor, Kalinga Institute of Industrial Technology University, Bhubaneswar, Odisha, India

Bighnaraj Naik

Bighnaraj Naik
Bighnaraj Naik is an Assistant Professor in the Department of Computer Application, Veer Surendra Sai University of Technology (Formerly UCE Burla), Odisha, India. He has published more than 100 research articles in various reputed peer reviewed International Journals, Conferences and Book Chapters. He has edited ten books from various international publishers such as Elsevier, Springer and IGI Global. At present, he has more than ten years of teaching experience in the field of Computer Science and Information Technology. He is a member of IEEE and his area of interest includes Data Science, Data Mining, Machine Learning, Deep Learning, Computational Intelligence and its applications in Science and Engineering. He has been serving as Guest Editor of various journal special issues in Information Fusion (Elsevier), Neural Computing and Applications (Springer), Evolutionary Intelligence (Springer), International Journal of Computational Intelligence Studies (Inderscience) and International Journal of Swarm Intelligence (Inderscience) etc. He is an active reviewer of various reputed journals from reputed publishers including IEEE Transactions, Elsevier, Springer and Inderscience etc. Currently, he is undertaking a major research project in the capacity of Principal Investigator, which is funded by Science and Engineering Research Board (SERB), Dept. of Science & Technology (DST), Govt. of India.

Affiliations and Expertise

Assistant Professor, Department of Computer Application, Veer Surrendra Sai University of Technology, Burla, India

H S Behera

Dr. Himansu Sekhar Behera is currently working as an Associate Professor and Head of the Department of Information Technology, Veer Surendra Sai University of Technology (VSSUT), India. He received his Doctor of Philosophy in Engineering (Ph.D.) from Biju Pattnaik University of Technology (BPUT), India. His research and development experience includes over 19 years in academia spanning different technical Institutes in India. His research interests include Data Mining, Soft Computing, Evolutionary Computation, Machine Intelligence and Distributed Systems. He has authored or co-authored over 100 research papers various international conferences and journals, as well as contributing several book chapters. He has edited 11 books and serves as an associate editor / member of the editorial board of various international journals and also guest edited 8 special issues on various topics of Inderscience and IGI Global Journals.

Affiliations and Expertise

Associate Professor, Veer Surendra Sai University of Technology, Burla, Sambulpar, Odisha, India

Ratings and Reviews

Write a review

There are currently no reviews for "Big Data Analytics for Intelligent Healthcare Management"