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_a10.1007/978-981-15-8097-0 _2doi |
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_aInternet of Medical Things for Smart Healthcare _h[electronic resource] : _bCovid-19 Pandemic / _cedited by Chinmay Chakraborty, Amit Banerjee, Lalit Garg, Joel J. P. C. Rodrigues. |
250 | _a1st ed. 2020. | ||
264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2020. |
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300 |
_aXII, 305 p. 200 illus., 177 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aStudies in Big Data, _x2197-6511 ; _v80 |
|
505 | 0 | _aChapter 1. Transmission Dynamics and Estimation of Basic Reproduction Number (R0) from Early Outbreak of Novel Coronavirus (COVID-19) in India -- Chapter 2. Covid -19 analysed by using machine deep learning -- Chapter 3. MML Classification Techniques for the pathogen based on pnuemonia-nCOVID-19 and the Detection of closely related lung diseases using Efficacious Learning Algorithms -- Chapter 4. Diagnosing COVID-19 Lung Inflammation using Machine Learning Algorithms: A Comparative Study -- Chapter 5. Factors Affecting the Success of Internet of Things for Enhancing Quality and Efficiency Implementation in Hospitals Sector in Jordan during the crises of Covid-19 -- Chapter 6. IoMT based Smart Diagnostic/Therapeutic Kit for Pandemic Patients -- Chapter 7. The Prediction Analysis of Covid-19 Cases using ARIMA and KALMAN Filter Models: A Case of Comparative Study -- Chapter 8. Exploration of cough recognition technologies grounded on sensors and artificial intelligence -- Chapter 9. A Review on use of Data Science for visualisation and prediction of the COVID-19 Pandemic and Early diagnosis of COVID-19 using Machine learning models -- Chapter 10. Fuzzy Cellular Automata Model For Discrete Dynamical System Representing Spread ofMERS And COVID-19 Virus, SumitaBasu and Sreeya Ghosh. | |
520 | _aThis book covers COVID-19 related research works and focuses on recent advances in the Internet of Things (IoT) in smart healthcare technologies. It includes reviews and original works on COVID-19 in terms of e-healthcare, medicine technology, life support systems, fast detection, diagnoses, developed technologies and innovative solutions, bioinformatics, datasets, apps for diagnosis, solutions for monitoring and control of the spread of COVID-19, among other topics. The book covers comprehensive studies from bioelectronics and biomedical engineering, artificial intelligence, and big data with a prime focus on COVID-19 pandemic. | ||
650 | 0 | _aComputational intelligence. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aBig data. | |
650 | 0 | _aMedical informatics. | |
650 | 1 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aArtificial Intelligence. |
650 | 2 | 4 | _aBig Data. |
650 | 2 | 4 | _aHealth Informatics. |
700 | 1 |
_aChakraborty, Chinmay. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aBanerjee, Amit. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aGarg, Lalit. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aRodrigues, Joel J. P. C. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9789811580963 |
776 | 0 | 8 |
_iPrinted edition: _z9789811580987 |
776 | 0 | 8 |
_iPrinted edition: _z9789811580994 |
830 | 0 |
_aStudies in Big Data, _x2197-6511 ; _v80 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-981-15-8097-0 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cSPRINGER | ||
999 |
_c179162 _d179162 |