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

Enregistré dans:
Détails bibliographiques
Auteur principal: Singh, S.K.. (Éditeur scientifique)
Autres auteurs: Singh, Ravi Shankar. (Éditeur scientifique), Pandey, A. K.., Udmale, Sandeep S.., Chaudhary, Ankit.
Support: E-Book
Langue: Anglais
Publié: San Diego, CA : Elsevier Science.
Autres localisations: Voir dans le Sudoc
Résumé: 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
Accès en ligne: Accès à l'E-book
LEADER 03598nmm a2200469 i 4500
001 ebook-280310919
005 20240917164722.0
007 cu|uuu---uuuuu
008 240917s2020||||us ||||g|||| ||||||eng d
020 |a 9780128214763 
035 |a (OCoLC)1456605655 
035 |a FRCYB88955498 
035 |a FRCYB26088955498 
035 |a FRCYB07488955498 
035 |a FRCYB29388955498 
035 |a FRCYB55488955498 
035 |a FRCYB55988955498 
035 |a FRCYB084688955498 
035 |a FRCYB087888955498 
035 |a FRCYB095788955498 
040 |a ABES  |b fre  |e AFNOR 
041 0 |a eng  |2 639-2 
100 1 |0 (IdRef)170016757  |1 http://www.idref.fr/170016757/id  |a Singh, S.K..  |4 edt.  |e Éditeur scientifique 
245 1 0 |a IoT-Based Data Analytics for the Healthcare Industry :  |b Techniques and Applications   |c [Edited by] Sanjay Kumar Singh, Ravi Shankar Singh, Anil Kumar Pandey, [et autres]. 
264 1 |a San Diego, CA :  |b Elsevier Science. 
264 2 |a Paris :  |b Cyberlibris,  |c 2020. 
336 |b txt  |2 rdacontent 
337 |b c  |2 rdamedia 
337 |b b  |2 isbdmedia 
338 |b ceb  |2 RDAfrCarrier 
500 |a Couverture (https://static2.cyberlibris.com/books_upload/136pix/9780128214763.jpg). 
506 |a L'accès en ligne est réservé aux établissements ou bibliothèques ayant souscrit l'abonnement  |e Cyberlibris 
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 
700 1 |a Singh, Ravi Shankar.  |4 edt.  |e Éditeur scientifique 
700 1 |0 (IdRef)120538296  |1 http://www.idref.fr/120538296/id  |a Pandey, A. K..  |4 edt.  |e Éditeur scientifique 
700 1 |a Udmale, Sandeep S..  |4 edt.  |e Éditeur scientifique 
700 1 |a Chaudhary, Ankit.  |4 edt.  |e Éditeur scientifique 
856 |q HTML  |u https://srvext.uco.fr/login?url=https://univ.scholarvox.com/book/88955498  |w Données éditeur  |z Accès à l'E-book 
886 2 |2 unimarc  |a 181  |a i#  |b xxxe## 
993 |a E-Book  
994 |a BNUM 
995 |a 280310919