COVID-19 Update: We are currently shipping orders daily. However, due to transit disruptions in some geographies, deliveries may be delayed. To provide all customers with timely access to content, we are offering 50% off Science and Technology Print & eBook bundle options. Terms & conditions.
Data Analytics in Biomedical Engineering and Healthcare - 1st Edition - ISBN: 9780128193143, 9780128193150

Data Analytics in Biomedical Engineering and Healthcare

1st Edition

Editors: Kun Lee Sanjiban Sekhar Roy Pijush Samui Vijay Kumar
Paperback ISBN: 9780128193143
eBook ISBN: 9780128193150
Imprint: Academic Press
Published Date: 16th October 2020
Page Count: 292
Sales tax will be calculated at check-out Price includes VAT/GST
150.00
127.50
131.00
240.91
115.00
Unavailable
Price includes VAT/GST

Institutional Subscription

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.

Description

Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book covers health analytics, data science, and machine and deep learning applications for biomedical data, covering areas such as predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction using predictive modeling. Case studies demonstrate big data applications in healthcare using the MapReduce and Hadoop frameworks.

Key Features

  • Examines the development and application of data analytics applications in biomedical data
  • Presents innovative classification and regression models for predicting various diseases
  • Discusses genome structure prediction using predictive modeling
  • Shows readers how to develop clinical decision support systems
  • Shows researchers and specialists how to use hybrid learning for better medical diagnosis, including case studies of healthcare applications using the MapReduce and Hadoop frameworks

Readership

Biomedical engineers, computer/data scientists, researchers and software engineers in the areas of data analytics, Artificial Intelligence, and machine learning

Table of Contents

1. Data analytics applications in biomedical data
2. Predictive Health Analysis
3. Exploration of EHR (Electronic Health Records) using data science
4. Machine Learning and Deep Learning application on medical image analysis
5. Developing Clinical Decision Support System
6. Innovative Classification, Regression Model for predicting various diseases
7. Computational Drug Discovery using State of the Art Unsupervised learning
8. Genome Structure prediction using Predictive modelling
9. Hybrid learning for better medical diagnosis
10. Big data application in healthcare under MapReduce and Hadoop frameworks

Details

No. of pages:
292
Language:
English
Copyright:
© Academic Press 2021
Published:
16th October 2020
Imprint:
Academic Press
Paperback ISBN:
9780128193143
eBook ISBN:
9780128193150

About the Editors

Kun Lee

1995-To date Full Professor SKK Business School Sungkyunkwan University Responsible for teaching Business Datamining, MIS (Management Information Systems), and Internet Business Models in undergraduate and graduate. I conduct several director positions for executive programs with Samsung Group. I am the quadruple winner of “The Sungkyunkwan University Outstanding Research Award”. In 2006 I received the university's highest research honor, “The Sungkyunkwan University Fellow Award" in recognition of extraordinary accomplishment in research and scholarship. Accordingly, I was honorably included in the Hall of Fame of the SKK Business School in 2007.

Affiliations and Expertise

Professor, SKK Business School, Sungkyunkwan University

Sanjiban Sekhar Roy

Sanjiban Sekhar Roy is an Associate Professor in the School of Computer Science and Engineering, Vellore Institute of Technology. He joined VIT in the year 2009 as an Asst. Professor. His research interests include Deep Learning and advanced machine learning. He has published around 50 articles in a reputed international journal (with SCI impact factors) and conferences. He also is editorial board members to a handful of international journals and reviewer to many highly reputed journals such as Neural processing letters, Springer , IEEE Access: The Multidisciplinary Open Access Journal, Computers & Security, Elsevier , International Journal of Advanced Intelligence Paradigms, Inderscience International publishers, International Journal of Artificial Intelligence and Soft Computing, Inderscience International publishers,Ad Hoc Networks, Elsevier, Evolutionary Intelligence, Springer, Journal of Ambient Intelligence and Humanized Computing, Springer, Iranian Journal of Science and Technology, Transactions of Electrical Engineering, Springer. He uses Deep Learning and machine learning techniques to solve many complex engineering problems, especially those are related to imagery. He is specialized in deep convolutional neural networks and generative adversarial network. Dr. Roy also has edited many books with reputed interntional publishers such as elsevier,springer and IGI Global. Very recently, Ministry of National Education, Romania in collaboration with "Aurel Vlaicu" University Arad Faculty of Engineers, Romania has awarded Dr. Roy with "Diploma of Excellence" as a sign of appreciation for the special achievements obtained in the scientific research activity in 2019.

Affiliations and Expertise

Associate Professor in School of Computer Science and Engineering, Vellore Institute of Technology

Pijush Samui

Professor Pijush Samui is Associate Professor at National Institute of Technology, Patna, India. He is an established researcher in the application of Artificial Intelligence (AI) for solving different problems in engineering. Samui has published journal articles, peer reviewed conference papers, book chapters and 4 books. He is also holding the position of Visiting Professor at Far East Federal University (Russia).

Affiliations and Expertise

Associate Professor, National Institute of Technology, Patna, India

Vijay Kumar

Dr. Vijay Kumar received M.Sc. degree in Electronics from the Magadh University, India 2003. He has completed a M.Tech degree in Microwave remote sensing systems from BIT Mesra, Ranchi, in 2005, and completed PhD from IIT Bombay, Mumbai in 2011 in Microwave Remote sensing. He worked as DST Govt. of India sponsored scientist/principal Investigator at CSRE, IIT Bombay during 2009 to 2013. He has been a visiting researcher at Earth observation Group, Northern Research Institute (NORUT) during 2009-2010. Presently, Kumar is working as Associate professor at School of Electronics Engineering, VIT University, Vellore TN, India from 2013 till date.

Affiliations and Expertise

Associate Professor, Microwave and Photonics Group, School of Electronics and Communication Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India

Ratings and Reviews