Description
Applications of Big Data in Healthcare: Theory and Practice begins with the basics of Big Data analysis and introduces the tools, processes and procedures associated with Big Data analytics. The book unites healthcare with Big Data analysis and uses the advantages of the latter to solve the problems faced by the former. The authors present the challenges faced by the healthcare industry, including capturing, storing, searching, sharing and analyzing data. This book illustrates the challenges in the applications of Big Data and suggests ways to overcome them, with a primary emphasis on data repositories, challenges, and concepts for data scientists, engineers and clinicians.
The applications of Big Data have grown tremendously within the past few years and its growth can not only be attributed to its competence to handle large data streams but also to its abilities to find insights from complex, noisy, heterogeneous, longitudinal and voluminous data. The main objectives of Big Data in the healthcare sector is to come up with ways to provide personalized healthcare to patients by taking into account the enormous amounts of already existing data.
- Provides case studies that illustrate the business processes underlying the use of big data and deep learning health analytics to improve health care delivery
- Supplies readers with a foundation for further specialized study in clinical analysis and data management
- Includes links to websites, videos, articles and other online content to expand and support the primary learning objectives for each major section of the book
Table of Contents
1.Big Data classification: techniques and tools 2.Big Data Analytics for healthcare: theory and applications 3.Application of tools and techniques of Big data analytics for healthcare system 4.Healthcare and medical Big Data analytics 5.Big Data analytics in medical imaging 6.Big Data analytics and artificial intelligence in mental healthcare 7.Big Data based breast cancer prediction using kernel support vector machine with the Gray Wolf Optimization algorithm 8.Big Data based medical data classification using oppositional Gray Wolf Optimization with kernel ridge regression 9.An analytical hierarchical process evaluation on parameters Apps-based Data Analytics for healthcare services 10.Firefly—Binary Cuckoo Search Technique based heart disease prediction in Big Data Analytics 11.Hybrid technique for heart diseases diagnosis based on convolution neural network and long short-term memory
