Internet of medical things for smart healthcare : Covid-19 pandemic / / Chinmay Chakraborty [and three others], editors |
Edizione | [1st ed. 2020.] |
Pubbl/distr/stampa | Singapore : , : Springer, , [2020] |
Descrizione fisica | 1 online resource (XII, 305 p. 200 illus., 177 illus. in color.) |
Disciplina | 610.285 |
Collana | Studies in big data |
Soggetto topico |
COVID-19 (Disease) - Health aspects
Medical care - Data processing Medical informatics |
ISBN | 981-15-8097-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Chapter 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. |
Record Nr. | UNINA-9910427673103321 |
Singapore : , : Springer, , [2020] | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Internet of medical things for smart healthcare : Covid-19 pandemic / / Chinmay Chakraborty [and three others], editors |
Edizione | [1st ed. 2020.] |
Pubbl/distr/stampa | Singapore : , : Springer, , [2020] |
Descrizione fisica | 1 online resource (XII, 305 p. 200 illus., 177 illus. in color.) |
Disciplina | 610.285 |
Collana | Studies in big data |
Soggetto topico |
COVID-19 (Disease) - Health aspects
Medical care - Data processing Medical informatics |
ISBN | 981-15-8097-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Chapter 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. |
Record Nr. | UNISA-996465447203316 |
Singapore : , : Springer, , [2020] | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
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