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Applications of Big Data in Healthcare
Theory and Practice
Examines the latest advances in applying Big Data, deep data learning and data analytics in healthcare delivery
Ashish Khanna (Edited by), Deepak Gupta (Edited by), Nilanjan Dey (Edited by)
9780128202036
Paperback, published 12 March 2021
310 pages, Approx. 120 illustrations
23.4 x 19 x 2 cm, 0.72 kg
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.
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
Subject Areas: Biomedical engineering [MQW]
