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020 a| 9780128181478q| (electronic bk.);

020 a| 0128181478q| (electronic bk.);

020 a| 9780128181461q| (electronic bk.);

020 a| 012818146Xq| (electronic bk.);

020 z| 9780128181461q| (paperback);

020 z| 012818146Xq| (paperback);

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245 00 a| Big data analytics for intelligent healthcare management /c| volume editors, Nilanjan Dey, Himansu Das, Bighnaraj Naik, Himansu Sekhar Behera.;

264 1 a| London :b| Academic Press, an imprint of Elsevier,c| [2019];

300 a| 1 online resource (xix, 292 pages) :b| illustrations.;

336 a| textb| txt2| rdacontent;

337 a| computerb| c2| rdamedia;

338 a| online resourceb| cr2| rdacarrier;

490 1 a| Advances in ubiquitous sensing applications for healthcare ;v| volume three;

504 a| Includes bibliographical references and index.;

505 0 a| Bio-inspired algorithms for big data analytics: a survey, taxonomy, and open challenges -- Big data analytics challenges and solutions -- Big data analytics in healthcare: a critical analysis -- Transfer learning and supervised classifier based prediction model for breast cancer -- Chronic TTH analysis by EMG and GSR biofeedback on various modes and various medical symptoms using IoT -- Multilevel classification framework of fMRI data: a big data approach -- Smart healthcare: an approach for ubiquitous healthcare management using IoT -- Blockchain in healthcare: challenges and solutions -- Intelligence-based health recommendation system using big data analytics -- Computational biology approach in management of big data of healthcare sector -- Kidney-inspired algorithm and fuzzy clustering for biomedical data analysis.;

520 a| Big Data Analytics for Intelligent Healthcare Management covers both the theory and application of hardware platforms and architectures, the development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of big data in healthcare and clinical research. The book provides the latest research findings on the use of big data analytics with statistical and machine learning techniques that analyze huge amounts of real-time healthcare data.;

588 0 a| Online resource; title from electronic title page (ProQuest Ebook Central, viewed October 25, 2019).;

650 0 a| Computer science.=| ^A267953;

650 0 a| Computer system failures.=| ^A455101;

650 0 a| Database management.=| ^A349280;

650 0 a| Data mining.=| ^A408868;

650 0 a| Image processing.=| ^A115874;

650 12 a| Big Data0| (DNLM)D000077558=| ^A1380382;

650 12 a| Data Miningx| methods0| (DNLM)D057225Q000379=| ^A1266906;

650 22 a| Data Sciencex| methods0| (DNLM)D000077488Q000379=| ^A1391323;

650 22 a| Computing Methodologies0| (DNLM)D003205=| ^A932886;

650 22 a| Biomedical Researchx| methods0| (DNLM)D035843Q000379=| ^A943524;

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650 7 a| Database management.2| fast0| (OCoLC)fst00888037;

650 7 a| Image processing.2| fast0| (OCoLC)fst00967501;

655 4 a| Electronic books.;

700 1 a| Dey, Nilanjan,d| 1984-e| editor.=| ^A1341437;

700 1 a| Das, Himansu,e| editor.=| ^A1393943;

700 1 a| Naik, Bighnaraj,e| editor.=| ^A1393947;

700 1 a| Behera, Himansu Sekhar,e| editor.=| ^A1394228;

830 0 a| Advances in ubiquitous sensing applications for healthcare ;v| volume three.=| ^A1394214;

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Big data analytics for intelligent healthcare management / volume editors, Nilanjan Dey, Himansu Das, Bighnaraj Naik, Himansu Sekhar Behera.

Format	Electronic
Publication	London : Academic Press, an imprint of Elsevier, [2019]
Copyright Date	©2019
Description	1 online resource (xix, 292 pages) : illustrations.
Supplemental Content	ProQuest Ebook Central
Subjects	Computer science. Computer system failures. Database management. Data mining. Image processing. Big Data Data Mining--methods. Data Science--methods. Computing Methodologies Biomedical Research--methods.

Other author/creator	Dey, Nilanjan, 1984- editor.
Other author/creator	Das, Himansu, editor.
Other author/creator	Naik, Bighnaraj, editor.
Other author/creator	Behera, Himansu Sekhar, editor.
Series	Advances in ubiquitous sensing applications for healthcare ; volume three Advances in ubiquitous sensing applications for healthcare ; volume three. ^A1394214
Contents	Bio-inspired algorithms for big data analytics: a survey, taxonomy, and open challenges -- Big data analytics challenges and solutions -- Big data analytics in healthcare: a critical analysis -- Transfer learning and supervised classifier based prediction model for breast cancer -- Chronic TTH analysis by EMG and GSR biofeedback on various modes and various medical symptoms using IoT -- Multilevel classification framework of fMRI data: a big data approach -- Smart healthcare: an approach for ubiquitous healthcare management using IoT -- Blockchain in healthcare: challenges and solutions -- Intelligence-based health recommendation system using big data analytics -- Computational biology approach in management of big data of healthcare sector -- Kidney-inspired algorithm and fuzzy clustering for biomedical data analysis.
Abstract	Big Data Analytics for Intelligent Healthcare Management covers both the theory and application of hardware platforms and architectures, the development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of big data in healthcare and clinical research. The book provides the latest research findings on the use of big data analytics with statistical and machine learning techniques that analyze huge amounts of real-time healthcare data.
Bibliography note	Includes bibliographical references and index.
Source of description	Online resource; title from electronic title page (ProQuest Ebook Central, viewed October 25, 2019).
Issued in other form	Print version: Big data analytics for intelligent healthcare management. London : Academic Press, [2019] 9780128181461
Genre/form	Electronic books.
ISBN	9780128181478 (electronic bk.)
ISBN	0128181478 (electronic bk.)
ISBN	9780128181461 (electronic bk.)
ISBN	012818146X (electronic bk.)
ISBN	(paperback)
ISBN	(paperback)
Stock number	9780128181478 Ingram Content Group

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Big data analytics for intelligent healthcare management / volume editors, Nilanjan Dey, Himansu Das, Bighnaraj Naik, Himansu Sekhar Behera.

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