Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics -

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Résumé :
Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians....

Biographie:
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...

Sommaire:
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...