Demystifying big data, machine learning, and deep learning for healthcare analytics

Table of Contents: Part I: Big Data in Healthcare Analytics 1. Foundations of Healthcare Informatics 2. Smart Healthcare Systems Using Big Data 3. Big Data-based Frameworks for Healthcare Systems 4. Predictive Analysis and Modelling in Healthcare Systems 5. Challenges and Opportunities of Big Data Integration in Patient-Centric Healthcare Analytics Using Mobile Networks 6. Emergence of Decision Support Systems in Healthcare Part II: Machine Learning and Deep Learning for Healthcare 7. A Comprehensive Review on Deep Learning Techniques for BCI-based Communication Systems 8. Machine Learning and Deep Learning-based Clinical Diagnostic Systems 9. An Improved Time-Frequency Method for Efficient Diagnosis of Cardiac Arrhythmias 10. Local Plastic Surgery-based Face Recognition Using Convolutional Neural Networks 11. Machine Learning Algorithms for Prediction of Heart Disease 12. Convolutional Siamese Networks for One-Shot Malaria Parasites Recognition in Microscopic Images 13. Kidney Disease Prediction Using a Machine Learning Approach: A Comparative and Comprehensive Analysis

This book explores the evolving landscape of data consumption, particularly in clinical healthcare. This book presents a variety of strategies, procedures, and algorithms for organising data in a structured fashion that will aid physicians in the treatment of patients and help biomedical engineers and computer scientists comprehend the influence of these techniques on healthcare analytics. The application chapters include a plethora of real-world case studies to serve as a reference for biomedical engineers, computer scientists, healthcare researchers, and doctors. Provides biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians with a comprehensive resource for understanding and developing healthcare analytics employing sophisticated techniques and technology. Contains in-depth illustrations of sophisticated methodologies via dataset samples, statistical tables, and graphs, as well as algorithms and computational strategies for designing new healthcare informatics applications. Unique case study technique provides readers with clinical implementation knowledge.