| TÃtulo : |
Internet of Medical Things for Smart Healthcare : Covid-19 Pandemic |
| Tipo de documento: |
documento electrónico |
| Autores: |
Chakraborty, Chinmay, ; Banerjee, Amit, ; Garg, Lalit, ; Rodrigues, Joel J. P. C., |
| Mención de edición: |
1 ed. |
| Editorial: |
Singapore [Malasia] : Springer |
| Fecha de publicación: |
2020 |
| Número de páginas: |
XII, 305 p. 200 ilustraciones, 177 ilustraciones en color. |
| ISBN/ISSN/DL: |
978-981-1580970-- |
| Nota general: |
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. |
| Idioma : |
Inglés (eng) |
| Palabras clave: |
Inteligencia Computacional Inteligencia artificial Grandes datos Informática Médica Informática de la Salud |
| Clasificación: |
006.3 |
| Resumen: |
Este libro cubre trabajos de investigación relacionados con COVID-19 y se centra en los avances recientes en el Internet de las cosas (IoT) en tecnologÃas sanitarias inteligentes. Incluye reseñas y trabajos originales sobre COVID-19 en términos de e-healthcare, tecnologÃa de la medicina, sistemas de soporte vital, detección rápida, diagnósticos, tecnologÃas desarrolladas y soluciones innovadoras, bioinformática, conjuntos de datos, aplicaciones para diagnóstico, soluciones para el seguimiento y control de la propagación del COVID-19, entre otros temas. El libro cubre estudios integrales de bioelectrónica e ingenierÃa biomédica, inteligencia artificial y big data con un enfoque principal en la pandemia de COVID-19. |
| Nota de contenido: |
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. |
| Tipo de medio : |
Computadora |
| Summary : |
This 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. |
| Enlace de acceso : |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
Internet of Medical Things for Smart Healthcare : Covid-19 Pandemic [documento electrónico] / Chakraborty, Chinmay, ; Banerjee, Amit, ; Garg, Lalit, ; Rodrigues, Joel J. P. C., . - 1 ed. . - Singapore [Malasia] : Springer, 2020 . - XII, 305 p. 200 ilustraciones, 177 ilustraciones en color. ISBN : 978-981-1580970-- Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés ( eng)
| Palabras clave: |
Inteligencia Computacional Inteligencia artificial Grandes datos Informática Médica Informática de la Salud |
| Clasificación: |
006.3 |
| Resumen: |
Este libro cubre trabajos de investigación relacionados con COVID-19 y se centra en los avances recientes en el Internet de las cosas (IoT) en tecnologÃas sanitarias inteligentes. Incluye reseñas y trabajos originales sobre COVID-19 en términos de e-healthcare, tecnologÃa de la medicina, sistemas de soporte vital, detección rápida, diagnósticos, tecnologÃas desarrolladas y soluciones innovadoras, bioinformática, conjuntos de datos, aplicaciones para diagnóstico, soluciones para el seguimiento y control de la propagación del COVID-19, entre otros temas. El libro cubre estudios integrales de bioelectrónica e ingenierÃa biomédica, inteligencia artificial y big data con un enfoque principal en la pandemia de COVID-19. |
| Nota de contenido: |
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. |
| Tipo de medio : |
Computadora |
| Summary : |
This 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. |
| Enlace de acceso : |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
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