Artificial Intelligence: Technology 4.0 as a solution for healthcare workers during COVID-19 pandemic
Author
Abstract
Suggested Citation
DOI: 10.32725/acta.2021.002
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.References listed on IDEAS
- Higor Leite & Ian R. Hodgkinson & Thorsten Gruber, 2020. "New development: ‘Healing at a distance’—telemedicine and COVID-19," Public Money & Management, Taylor & Francis Journals, vol. 40(6), pages 483-485, July.
- da Silva, Ramon Gomes & Ribeiro, Matheus Henrique Dal Molin & Mariani, Viviana Cocco & Coelho, Leandro dos Santos, 2020. "Forecasting Brazilian and American COVID-19 cases based on artificial intelligence coupled with climatic exogenous variables," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
- Lalmuanawma, Samuel & Hussain, Jamal & Chhakchhuak, Lalrinfela, 2020. "Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Anuj Kumar & T. Sowdamini & Sanjay Manocha & Purvi Pujari, 2021. "Gamification as a Sustainable Tool for HR Managers," Acta Universitatis Bohemiae Meridionalis, University of South Bohemia in Ceske Budejovice, Faculty of Economics, vol. 24(2), pages 1-14.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Tayarani N., Mohammad-H., 2021. "Applications of artificial intelligence in battling against covid-19: A literature review," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
- Andrés Rodríguez‐Pose & Chiara Burlina, 2021.
"Institutions and the uneven geography of the first wave of the COVID‐19 pandemic,"
Journal of Regional Science, Wiley Blackwell, vol. 61(4), pages 728-752, September.
- RodrÃguez-Pose, Andrés & Burlina, Chiara, 2020. "Institutions and the uneven geography of the first wave of the COVID-19 pandemic," CEPR Discussion Papers 15443, C.E.P.R. Discussion Papers.
- Andrés Rodrìguez-Pose & Chiara Burlina, 2020. "Institutions and the uneven geography of the first wave of the COVID-19 pandemic," Discussion Paper series in Regional Science & Economic Geography 2020-09, Gran Sasso Science Institute, Social Sciences, revised Nov 2020.
- Rodríguez-Pose, Andrés & Burlina, Chiara, 2021. "Institutions and the uneven geography of the first wave of the COVID-19 pandemic," LSE Research Online Documents on Economics 110454, London School of Economics and Political Science, LSE Library.
- Andres Rodriguez-Pose & Chiara Burlina, 2020. "Institutions and the uneven geography of the first wave of the COVID-19 pandemic," Papers in Evolutionary Economic Geography (PEEG) 2051, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Nov 2020.
- Rodríguez-Pose, Andrés & Burlina, Chiara, 2020. "Institutions and the uneven geography of the first wave of the COVID-19 pandemic," LSE Research Online Documents on Economics 107499, London School of Economics and Political Science, LSE Library.
- Srinka Basu & Sugata Sen, 2023. "COVID 19 Pandemic, Socio-Economic Behaviour and Infection Characteristics: An Inter-Country Predictive Study Using Deep Learning," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 645-676, February.
- Faizeh Hatami & Shi Chen & Rajib Paul & Jean-Claude Thill, 2022. "Simulating and Forecasting the COVID-19 Spread in a U.S. Metropolitan Region with a Spatial SEIR Model," IJERPH, MDPI, vol. 19(23), pages 1-16, November.
- Mohammad Reza Davahli & Krzysztof Fiok & Waldemar Karwowski & Awad M. Aljuaid & Redha Taiar, 2021. "Predicting the Dynamics of the COVID-19 Pandemic in the United States Using Graph Theory-Based Neural Networks," IJERPH, MDPI, vol. 18(7), pages 1-12, April.
- Ehab M. Almetwally, 2022. "The Odd Weibull Inverse Topp–Leone Distribution with Applications to COVID-19 Data," Annals of Data Science, Springer, vol. 9(1), pages 121-140, February.
- Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2023. "Which COVID-19 information really impacts stock markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
- Dalton Garcia Borges de Souza & Erivelton Antonio dos Santos & Francisco Tarcísio Alves Júnior & Mariá Cristina Vasconcelos Nascimento, 2021. "On Comparing Cross-Validated Forecasting Models with a Novel Fuzzy-TOPSIS Metric: A COVID-19 Case Study," Sustainability, MDPI, vol. 13(24), pages 1-25, December.
- Beniamino Callegari & Christophe Feder, 2022. "Entrepreneurship and the systemic consequences of epidemics: A literature review and emerging model," International Entrepreneurship and Management Journal, Springer, vol. 18(4), pages 1653-1684, December.
- Ribeiro-Navarrete, Samuel & Saura, Jose Ramon & Palacios-Marqués, Daniel, 2021. "Towards a new era of mass data collection: Assessing pandemic surveillance technologies to preserve user privacy," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
- Medeiros, Marcelo C. & Street, Alexandre & Valladão, Davi & Vasconcelos, Gabriel & Zilberman, Eduardo, 2022.
"Short-term Covid-19 forecast for latecomers,"
International Journal of Forecasting, Elsevier, vol. 38(2), pages 467-488.
- Marcelo Medeiros & Alexandre Street & Davi Vallad~ao & Gabriel Vasconcelos & Eduardo Zilberman, 2020. "Short-Term Covid-19 Forecast for Latecomers," Papers 2004.07977, arXiv.org, revised Sep 2021.
- Khlystova, Olena & Kalyuzhnova, Yelena & Belitski, Maksim, 2022. "The impact of the COVID-19 pandemic on the creative industries: A literature review and future research agenda," Journal of Business Research, Elsevier, vol. 139(C), pages 1192-1210.
- Barraza, Néstor Ruben & Pena, Gabriel & Moreno, Verónica, 2020. "A non-homogeneous Markov early epidemic growth dynamics model. Application to the SARS-CoV-2 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
- Rohitash Chandra & Yixuan He, 2021. "Bayesian neural networks for stock price forecasting before and during COVID-19 pandemic," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-32, July.
- Yao, Haitang & Liu, Wei & Wu, Chia-Huei & Yuan, Yu-Hsi, 2022. "The imprinting effect of SARS experience on the fear of COVID-19: The role of AI and big data," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
- Wajdi Aljedaani & Eysha Saad & Furqan Rustam & Isabel de la Torre Díez & Imran Ashraf, 2022. "Role of Artificial Intelligence for Analysis of COVID-19 Vaccination-Related Tweets: Opportunities, Challenges, and Future Trends," Mathematics, MDPI, vol. 10(17), pages 1-33, September.
- El-Sayed A El-Sherpieny & Ehab M Almetwally & Abdisalam Hassan Muse & Eslam Hussam, 2023. "Data analysis for COVID-19 deaths using a novel statistical model: Simulation and fuzzy application," PLOS ONE, Public Library of Science, vol. 18(4), pages 1-17, April.
- da Silva, Ramon Gomes & Ribeiro, Matheus Henrique Dal Molin & Moreno, Sinvaldo Rodrigues & Mariani, Viviana Cocco & Coelho, Leandro dos Santos, 2021. "A novel decomposition-ensemble learning framework for multi-step ahead wind energy forecasting," Energy, Elsevier, vol. 216(C).
- Karime Chahuán-Jiménez & Rolando Rubilar-Torrealba & Hanns de la Fuente-Mella, 2021. "Market Openness and Its Relationship to Connecting Markets Due to COVID-19," Sustainability, MDPI, vol. 13(19), pages 1-12, October.
- Ortiz-Barrios, Miguel & Arias-Fonseca, Sebastián & Ishizaka, Alessio & Barbati, Maria & Avendaño-Collante, Betty & Navarro-Jiménez, Eduardo, 2023. "Artificial intelligence and discrete-event simulation for capacity management of intensive care units during the Covid-19 pandemic: A case study," Journal of Business Research, Elsevier, vol. 160(C).
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:boh:actaub:v:24:y:2021:i:1:p:19-35. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ivo Andrle (email available below). General contact details of provider: https://edirc.repec.org/data/efjcucz.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.