Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics
Langue : Anglais
Coordonnateurs : N Pradeep, Kautish Sandeep, Peng Sheng-Lung
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.
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
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
Dr. Pradeep N PhD is Associate Professor in Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, Karnataka, India affiliated Visvesvaraya Technological University, Belagavi, Karnataka, India. He has 18 years of academic experience, including teaching and research experience. His research areas of interest include machine learning, pattern recognition, medical image analysis, knowledge discovery techniques, and data analytics. He has published more than 20 research articles published in refereed journals, authored six book chapters, and edited several books. He is a reviewer of various international conferences and several journals, including Multimedia Tools and Applications, Springer. His one Indian patent application is published and one Australian patent is granted. He is a professional member in ACM, ISTE and IEI. He was awarded as "Outstanding Teacher in Computer Science and Engineering", during the 3rd Global Outreach Research and Education Summit and Awards 2019, organized by Global Outreach Research and Education Association. Dr. Pradeep N is a technical committee member for Davangere Smart City, Davangere.
Sandeep Kautish, PhD is Professor and Director at Apex Institute of Technology (AIT-CSE), Chandigarh University, Punjab India and an academician by choice and has more than 20 years of full-time experience in teaching and research. He has been associated with Asia Pacific University Malaysia for over five years at their TNE site at Kathmandu Nepal in the capacity of Director-Academics. He earned his doctorate degree in Computer Science on Intelligent Systems in Social Networks. He has over 100 publications and his research works have been published in highly reputed journals, i.e., IEEE Transaction of Industrial Informatics, IEEE Access, and Multimedia Tools and Applications, etc. Dr. Kautish has edited 24 books with leading publishers, i.e., Elsevier, Springer, Emerald, and IGI Global, and is a
- Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies
- Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics
- Unique case study approach provides readers with insights for practical clinical implementation
Date de parution : 06-2021
Ouvrage de 372 p.
19x23.3 cm
Thèmes de Demystifying Big Data, Machine Learning, and Deep... :
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