IoT-based data analytics for the healthcare industry techniques and applications / edited by Sanjay Kumar Singh, Ravi Shankar Singh, Anil Kumar Pandey, Sandeep S. Udmale, Ankit Chaudhary.

Format Electronic
Publication InfoAmsterdam : Academic Press, 2021.
Descriptionxx, 320 pages : illustrations (some color) ; 24 cm.
Supplemental ContentFull text available from eBooks on EBSCOhost
Supplemental ContentFull text available from eBook - Engineering 2021 [EBCE21]
Subjects

Other author/creatorSingh, S. K. (Sanjay Kumar)
Other author/creatorSingh, Ravi Shankar.
Other author/creatorPandey, Anil Kumar.
Other author/creatorUdmale, Sandeep S.
Other author/creatorChaudhary, Ankit.
SeriesIntelligent data centric systems
Intelligent data centric systems. ^A1334749
Abstract IoT Based Data Analytics for the Healthcare Industry: Techniques and Applications explores recent advances in the analysis of healthcare industry data through IoT data analytics. The book covers the analysis of ubiquitous data generated by the healthcare industry, from a wide range of sources, including patients, doctors, hospitals, and health insurance companies. The book provides AI solutions and support for healthcare industry end-users who need to analyze and manipulate this vast amount of data. These solutions feature deep learning and a wide range of intelligent methods, including simulated annealing, tabu search, genetic algorithm, ant colony optimization, and particle swarm optimization. The book also explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages, challenges and issues in data collection, data handling, and data collection set-up. Healthcare industry data or streaming data generated by ubiquitous sensors cocooned into the IoT requires advanced analytics to transform data into information. With advances in computing power, communications, and techniques for data acquisition, the need for advanced data analytics is in high demand.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Issued in other formebook version : 9780128214763
Genre/formElectronic books.
LCCN 2020940966
ISBN9780128214725 paperback
ISBN0128214724 paperback
ISBNelectronic publication

Availability

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Electronic Resources ✔ Available