Big Data Analytics for Healthcare: Datasets, Techniques, Life Cycles, Management, and Applications

Keikhosrokiani, Pantea

ISBN 10: 0323919073 / ISBN 13: 9780323919074

Published by Academic Press (edition 1), 2022

About this Item

It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.

Seller Inventory # 0323919073-11-1

Bibliographic Details

• Title: Big Data Analytics for Healthcare: Datasets, Techniques, Life Cycles, Management, and Applications
• Publisher: Academic Press (edition 1)
• Publication Date: 2022
• Language: English
• ISBN 10: 0323919073
• ISBN 13: 9780323919074
• Binding: Paperback
• Edition: 1.
• Condition: Good

About this title

Synopsis

Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases. The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths. It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work.

• Presents theories, methods and approaches in which data analytic techniques are used for medical data
• Brings practical information on how to use big data for classification, diagnosis, treatment, and prediction of diseases
• Discusses social, behavioral, and medical fake news analytics for medical information systems

About the Author

Pantea Keikhosrokiani is a Senior Lecturer at the School of Computer Sciences, Universiti Sains Malaysia (USM; Penang, Malaysia). She was a teaching fellow at the National Advanced IPv6 Centre of Excellence (Nav6), USM. She has received her PhD in Service System Engineering, Information System, and her master’s degree in information technology from the School of Computer Sciences, USM. She has been graduated in Bachelor of Science in Electrical Engineering Electronics. Her articles have been published in distinguished edited books and journals including Elsevier (Telematics & Informatics), Springer (Cognition, Technology, & Work), Taylors and Francis and IGI global, and have been indexed by ISI, Scopus and PubMed. Her recent book is published by Elsevier entitled Perspectives in The Development of Mobile Medical Information Systems: Life Cycle, Management, Methodological Approach and Application. Her areas of interest for research and teaching are Information Systems Development, Behavior-change support systems, Database Systems, Health and Medical Informatics, Business Informatics, Location-Based Mobile Applications, Big Data, and Technopreneurship.