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.- 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
Table of Contents
1. Bio-Inspired Algorithms for Big Data Analytics: A Survey, Taxonomy, and Open Challenges2. Big Data Analytics Challenges and Solutions3. Big Data Analytics in Healthcare: A Critical Analysis4. Transfer Learning and Supervised Classifier Based Prediction Model for Breast Cancer5. Chronic TTH Analysis by EMG and GSR Biofeedback on Various Modes and Various Medical Symptoms Using IoT6. Multilevel Classification Framework of fMRI Data: A Big Data Approach7. Smart Healthcare: An Approach for Ubiquitous Healthcare Management Using IOT8. Blockchain in Healthcare: Challenges and Solutions9. Intelligence-Based Health Recommendation System Using Big Data Analytics10. Computational Biology Approach in Management of Big Data of Healthcare Sector11. Kidney-Inspired Algorithm and Fuzzy Clustering for Biomedical Data Analysis
