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Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review

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Cited by:

  1. Marcel Lucas Chee & Marcus Eng Hock Ong & Fahad Javaid Siddiqui & Zhongheng Zhang & Shir Lynn Lim & Andrew Fu Wah Ho & Nan Liu, 2021. "Artificial Intelligence Applications for COVID-19 in Intensive Care and Emergency Settings: A Systematic Review," IJERPH, MDPI, vol. 18(9), pages 1-15, April.
  2. 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.
  3. Esraa Faisal Malik & Khai Wah Khaw & Bahari Belaton & Wai Peng Wong & XinYing Chew, 2022. "Credit Card Fraud Detection Using a New Hybrid Machine Learning Architecture," Mathematics, MDPI, vol. 10(9), pages 1-16, April.
  4. 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.
  5. 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.
  6. Yan, Tao & Wong, Pak Kin & Ren, Hao & Wang, Huaqiao & Wang, Jiangtao & Li, Yang, 2020. "Automatic distinction between COVID-19 and common pneumonia using multi-scale convolutional neural network on chest CT scans," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
  7. Wang, Lingxiao & Hare, Brian M. & Zhou, Kai & Stöcker, Horst & Scholten, Olaf, 2023. "Identifying lightning structures via machine learning," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
  8. 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).
  9. 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.
  10. Miraj Ahmed Bhuiyan & Tiziana Crovella & Annarita Paiano & Helena Alves, 2021. "A Review of Research on Tourism Industry, Economic Crisis and Mitigation Process of the Loss: Analysis on Pre, During and Post Pandemic Situation," Sustainability, MDPI, vol. 13(18), pages 1-27, September.
  11. Jonathan S. Talahua & Jorge Buele & P. Calvopiña & José Varela-Aldás, 2021. "Facial Recognition System for People with and without Face Mask in Times of the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
  12. 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.
  13. Manuel Sánchez-Montañés & Pablo Rodríguez-Belenguer & Antonio J. Serrano-López & Emilio Soria-Olivas & Yasser Alakhdar-Mohmara, 2020. "Machine Learning for Mortality Analysis in Patients with COVID-19," IJERPH, MDPI, vol. 17(22), pages 1-20, November.
  14. 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.
  15. Tayarani N., Mohammad-H., 2021. "Applications of artificial intelligence in battling against covid-19: A literature review," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
  16. Mario A Quiroz-Juárez & Armando Torres-Gómez & Irma Hoyo-Ulloa & Roberto de J León-Montiel & Alfred B U’Ren, 2021. "Identification of high-risk COVID-19 patients using machine learning," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-21, September.
  17. Sini V. Pillai & Ranjith S. Kumar, 2021. "The role of data-driven artificial intelligence on COVID-19 disease management in public sphere: a review," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 48(4), pages 375-389, December.
  18. 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).
  19. Syed Kashif Badshah1Noor Badshah, 2024. "Classification of Medical Images Through Convolutional Neural Network Modification Method," International Journal of Innovations in Science & Technology, 50sea, vol. 6(5), pages 216-226, May.
  20. Sonsare, Pravinkumar M. & C, Gunavathi, 2021. "Cascading 1D-Convnet Bidirectional Long Short Term Memory Network with Modified COCOB Optimizer: A Novel Approach for Protein Secondary Structure Prediction," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
  21. 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).
  22. Yuki Furuse & Yura K. Ko & Kota Ninomiya & Motoi Suzuki & Hitoshi Oshitani, 2021. "Relationship of Test Positivity Rates with COVID-19 Epidemic Dynamics," IJERPH, MDPI, vol. 18(9), pages 1-10, April.
  23. Anuj Kumar & Purvi Pujari & Nimit Gupta, 2021. "Artificial Intelligence: Technology 4.0 as a solution for healthcare workers during COVID-19 pandemic," Acta Universitatis Bohemiae Meridionalis, University of South Bohemia in Ceske Budejovice, Faculty of Economics, vol. 24(1), pages 19-35.
  24. Aggarwal, Sakshi, 2023. "Machine Learning algorithms, perspectives, and real-world application: Empirical evidence from United States trade data," MPRA Paper 116579, University Library of Munich, Germany.
  25. 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.
  26. Anil Babu Payedimarri & Diego Concina & Luigi Portinale & Massimo Canonico & Deborah Seys & Kris Vanhaecht & Massimiliano Panella, 2021. "Prediction Models for Public Health Containment Measures on COVID-19 Using Artificial Intelligence and Machine Learning: A Systematic Review," IJERPH, MDPI, vol. 18(9), pages 1-11, April.
  27. Sharov, Konstantin S., 2020. "Creating and applying SIR modified compartmental model for calculation of COVID-19 lockdown efficiency," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
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