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Assessing COVID-19 and other pandemics and epidemics using computational modelling and data analysis / / Subhendu Kumar Pani [and four others], editors
| Assessing COVID-19 and other pandemics and epidemics using computational modelling and data analysis / / Subhendu Kumar Pani [and four others], editors |
| Autore | Hooper Jane <1981-> |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (416 pages) |
| Disciplina | 006.3 |
| Soggetto topico | Artificial intelligence |
| ISBN | 3-030-79753-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464553203316 |
Hooper Jane <1981->
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| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis / / edited by Subhendu Kumar Pani, Sujata Dash, Wellington P. dos Santos, Syed Ahmad Chan Bukhari, Francesco Flammini
| Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis / / edited by Subhendu Kumar Pani, Sujata Dash, Wellington P. dos Santos, Syed Ahmad Chan Bukhari, Francesco Flammini |
| Autore | Hooper Jane <1981-> |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (416 pages) |
| Disciplina | 006.3 |
| Collana | Computer Science Series |
| Soggetto topico |
Artificial intelligence
Quantitative research Cooperating objects (Computer systems) Internet of things Public health Diseases - Animal models Artificial Intelligence Data Analysis and Big Data Cyber-Physical Systems Internet of Things Public Health Disease Models |
| ISBN | 3-030-79753-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1 Artificial Intelligence (AI) and Big Data Analytics for COVID-19 Pandemic -- Chapter 2 COVID-19 TravelCover Post-lockdown Smart Transportation Management System for COVID-19 -- Chapter 3 Diverse techniques applied for effective diagnosis of COVID 19 -- Chapter 4 A Review on Detection of Covid-19 Patients using Deep Learning Techniques.-Chapter 5 Internet of Health Things (IoHT) for COVID 19 -- Chapter 6 Diagnosis for COVID-19 -- Chapter 7 IoT in Combating Covid 19 Pandemics Lessons for Developing Countries -- Chapter 8 Machine learning approaches for COVID 19 pandemic -- Chapter 9 Smart sensing for COVID 19 Pandemic -- Chapter 10 eHealth, mHealth and Telemedicine for COVID-19 pandemic -- Chapter 11 Prediction of care for patients in a Covid-19 pandemic situation based on haematological parameters -- Chapter 12 Bioinformatics in Diagnosis of Covid-19 -- Chapter 13 Predicting the Covid-19 Morbidity Outspread and Mortality Using Deep Learning Techniques -- Chapter 14 LSTM -CNN Deep learning Based Hybrid system for real time COVID-19 data analysis and prediction using Twitter data -- Chapter 15 An intelligent tool to support diagnosis of Covid-19 by texture analysis of computerized tomography x-ray images and machine learning -- Chapter 16 Analysis of Blockchain Backed Covid19 Data -- Chapter 17 Intelligent systems for dengue, chikungunya and zika temporal and spatio-temporal forecasting a contribution and a brief review -- Chapter 18 Machine learning approaches for temporal and spatio-temporal Covid-19 forecasting a brief review and a contribution -- Chapter 19 Image Reconstruction for COVID-19 using Multi-frequency Electrical Impedance Tomography. |
| Record Nr. | UNINA-9910522955603321 |
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Hooper Jane <1981->
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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