Big Data Analytics for Intelligent Healthcare Management

A comprehensive guide to the application of Big Data analytics for biomedical engineering and clinical and healthcare research and management

Nilanjan Dey (Edited by), Himansu Das (Edited by), Bighnaraj Naik (Edited by), H S Behera (Edited by)

9780128181461, Elsevier Science

Paperback, published 13 April 2019

312 pages
23.4 x 19 x 2 cm, 0.66 kg

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.

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

Subject Areas: Biomedical engineering [MQW]