Big Data Analytics in Healthcare

Anand J. Kulkarni

ISBN 10: 3030316718 / ISBN 13: 9783030316716

Published by Springer International Publishing, Springer International Publishing Okt 2019, 2019

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers, scientists, and students studying/involved in the development of big data tools in the areas of healthcare and medicine. It also features a multifaceted and state-of-the-art literature review on healthcare data, its modalities, complexities, and methodologies, along with mathematical formulations. The book is divided into two main sections, the first of which discusses the challenges and opportunities associated with the implementation of big data in the healthcare sector. In turn, the second addresses the mathematical modeling of healthcare problems, as well as current and potential future big data applications and platforms. 200 pp. Englisch.

Seller Inventory # 9783030316716

Bibliographic Details

• Title: Big Data Analytics in Healthcare
• Publisher: Springer International Publishing, Springer International Publishing Okt 2019
• Publication Date: 2019
• Language: English
• ISBN 10: 3030316718
• ISBN 13: 9783030316716
• Binding: Buch
• Condition: Neu

About this title

Synopsis

This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers, scientists, and students studying/involved in the development of big data tools in the areas of healthcare and medicine. It also features a multifaceted and state-of-the-art literature review on healthcare data, its modalities, complexities, and methodologies, along with mathematical formulations.

The book is divided into two main sections, the first of which discusses the challenges and opportunities associated with the implementation of big data in the healthcare sector. In turn, the second addresses the mathematical modeling of healthcare problems, as well as current and potential future big data applications and platforms.