IoT-Based Data Analytics for the Healthcare Industry : Techniques and Applications

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, inclu...

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Glavni avtor: Singh, S.K
Drugi avtorji: Singh, Ravi Shankar (Éditeur intellectuel), Pandey, A. K. (Éditeur intellectuel), Udmale, Sandeep S. (Éditeur intellectuel), Chaudhary, Ankit (Éditeur intellectuel)
Format: Livre numérique
Jezik:Anglais
Izdano: San Diego, CA : Elsevier Science 2020.
Paris : Cyberlibris
Online dostop:Accès Université d'Orléans et IFPM
Accès INSA CVL
Sporočilo: Couverture. https://static2.cyberlibris.com/books_upload/136pix/9780128214763.jpg
Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur
Cyberlibris (ScholarVox) corpus Sciences de l'ingénieur
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• IoT-Based Data Analytics for the Healthcare Industry, Techniques and Applications, [Edited by] Sanjay Kumar Singh, Ravi Shankar Singh, Anil Kumar Pandey, [et autres], San Diego, CA, Elsevier Science, 2020, 1 vol. (482 p.), 978-01-2821-472-5
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520 |a 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. Provides state-of-art methods and current trends in data analytics for the healthcare industry Addresses the top concerns in the healthcare industry using IoT and data analytics, and machine learning and deep learning techniques Discusses several potential AI techniques developed using IoT for the healthcare industry Explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages 
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700 1 |a Chaudhary, Ankit.  |4 edt 
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