Published on in Vol 22, No 12 (2020): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20756, first published .
Artificial Intelligence in the Fight Against COVID-19: Scoping Review

Artificial Intelligence in the Fight Against COVID-19: Scoping Review

Artificial Intelligence in the Fight Against COVID-19: Scoping Review

Journals

  1. Abd-alrazaq A, Alajlani M, Alhuwail D, Erbad A, Giannicchi A, Shah Z, Hamdi M, Househ M. Blockchain technologies to mitigate COVID-19 challenges: A scoping review. Computer Methods and Programs in Biomedicine Update 2021;1:100001 View
  2. Abd-Alrazaq A, Schneider J, Mifsud B, Alam T, Househ M, Hamdi M, Shah Z. A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis. Journal of Medical Internet Research 2021;23(3):e23703 View
  3. Kumar V, Singh D, Kaur M, Damaševičius R. Overview of current state of research on the application of artificial intelligence techniques for COVID-19. PeerJ Computer Science 2021;7:e564 View
  4. Abd-Alrazaq A, Hassan A, Abuelezz I, Ahmed A, Alzubaidi M, Shah U, Alhuwail D, Giannicchi A, Househ M. Overview of Technologies Implemented During the First Wave of the COVID-19 Pandemic: Scoping Review. Journal of Medical Internet Research 2021;23(9):e29136 View
  5. Valtchev S, Asgary A, Chen M, Cronemberger F, Najafabadi M, Cojocaru M, Wu J. Managing SARS-CoV-2 Testing in Schools with an Artificial Intelligence Model and Application Developed by Simulation Data. Electronics 2021;10(14):1626 View
  6. Adadi A, Lahmer M, Nasiri S. Artificial Intelligence and COVID-19: A Systematic umbrella review and roads ahead. Journal of King Saud University - Computer and Information Sciences 2022;34(8):5898 View
  7. Alzubaidi M, Zubaydi H, Bin-Salem A, Abd-Alrazaq A, Ahmed A, Househ M. Role of deep learning in early detection of COVID-19: Scoping review. Computer Methods and Programs in Biomedicine Update 2021;1:100025 View
  8. Ali H, Shah Z. Combating COVID-19 Using Generative Adversarial Networks and Artificial Intelligence for Medical Images: Scoping Review. JMIR Medical Informatics 2022;10(6):e37365 View
  9. Jiao Z, Ji H, Yan J, Qi X. Application of big data and artificial intelligence in epidemic surveillance and containment. Intelligent Medicine 2023;3(1):36 View
  10. Yu C, Helwig E. Role of rehabilitation amidst the COVID-19 pandemic: a review. Journal of Translational Medicine 2021;19(1) View
  11. Loveys K, Sagar M, Pickering I, Broadbent E. A Digital Human for Delivering a Remote Loneliness and Stress Intervention to At-Risk Younger and Older Adults During the COVID-19 Pandemic: Randomized Pilot Trial. JMIR Mental Health 2021;8(11):e31586 View
  12. Uthman O, Adetokunboh O, Wiysonge C, Al-Awlaqi S, Hanefeld J, El Bcheraoui C. Classification Schemes of COVID-19 High Risk Areas and Resulting Policies: A Rapid Review. Frontiers in Public Health 2022;10 View
  13. Woo J, Kim E, Kim S. The current status of breakthrough devices designation in the United States and innovative medical devices designation in Korea for digital health software. Expert Review of Medical Devices 2022;19(3):213 View
  14. Chen W, Yao M, Zhu Z, Sun Y, Han X. The application research of AI image recognition and processing technology in the early diagnosis of the COVID-19. BMC Medical Imaging 2022;22(1) View
  15. Selvaraj C, Chandra I, Singh S. Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries. Molecular Diversity 2022;26(3):1893 View
  16. Majeed A, Hwang S. Data-Driven Analytics Leveraging Artificial Intelligence in the Era of COVID-19: An Insightful Review of Recent Developments. Symmetry 2021;14(1):16 View
  17. Imami A, McCullumsmith R, O’Donovan S. Strategies to identify candidate repurposable drugs: COVID-19 treatment as a case example. Translational Psychiatry 2021;11(1) View
  18. Mattiuzzi C, Lippi G. The Global Impact of COVID-19 on Threat Appraisals. Healthcare 2022;10(9):1718 View
  19. Abd-alrazaq A, Abuelezz I, Hassan A, AlSammarraie A, Alhuwail D, Irshaidat S, Abu Serhan H, Ahmed A, Alabed Alrazak S, Househ M. Artificial Intelligence–Driven Serious Games in Health Care: Scoping Review. JMIR Serious Games 2022;10(4):e39840 View
  20. Bartlett L, Pirrone A, Javed N, Gobet F. Computational Scientific Discovery in Psychology. Perspectives on Psychological Science 2023;18(1):178 View
  21. Horvath A, Lind T, Frece N, Wurzer H, Stadlbauer V. Validation of a simple risk stratification tool for COVID-19 mortality. Frontiers in Medicine 2022;9 View
  22. Comito C, Pizzuti C. Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review. Artificial Intelligence in Medicine 2022;128:102286 View
  23. Ferrari E, Gargani L, Barbieri G, Ghiadoni L, Faita F, Bacciu D, Rapallo F. A causal learning framework for the analysis and interpretation of COVID-19 clinical data. PLOS ONE 2022;17(5):e0268327 View
  24. Bashar A, Latif G, Ben Brahim G, Mohammad N, Alghazo J. COVID-19 Pneumonia Detection Using Optimized Deep Learning Techniques. Diagnostics 2021;11(11):1972 View
  25. El-Sherif D, Abouzid M. Analysis of mHealth research: mapping the relationship between mobile apps technology and healthcare during COVID-19 outbreak. Globalization and Health 2022;18(1) View
  26. Al-Garadi M, Yang Y, Sarker A. The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges. Healthcare 2022;10(11):2270 View
  27. Hassoun S, Jefferson F, Shi X, Stucky B, Wang J, Rosa E. Artificial Intelligence for Biology. Integrative and Comparative Biology 2022;61(6):2267 View
  28. Semenova Y, Trenina V, Pivina L, Glushkova N, Zhunussov Y, Ospanov E, Bjørklund G. The lessons of COVID-19, SARS, and MERS: Implications for preventive strategies. International Journal of Healthcare Management 2022;15(4):314 View
  29. Al Khalili S, Al Maani A, Al Wahaibi A, Al Yaquobi F, Al-Jardani A, Al Harthi K, Alqayoudhi A, Al Manji A, Al Rawahi B, Al-Abri S. Challenges and Opportunities for Public Health Service in Oman From the COVID-19 Pandemic: Learning Lessons for a Better Future. Frontiers in Public Health 2021;9 View
  30. Mele C, Marzullo M, Morande S, Spena T. How Artificial Intelligence Enhances Human Learning Abilities: Opportunities in the Fight Against COVID-19. Service Science 2022;14(2):77 View
  31. Stara V, Vera B, Bolliger D, Paolini S, de Jong M, Felici E, Koenderink S, Rossi L, Von Doellen V, di Rosa M. Toward the Integration of Technology-Based Interventions in the Care Pathway for People with Dementia: A Cross-National Study. International Journal of Environmental Research and Public Health 2021;18(19):10405 View
  32. Martinez-Millana A, Saez-Saez A, Tornero-Costa R, Azzopardi-Muscat N, Traver V, Novillo-Ortiz D. Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews. International Journal of Medical Informatics 2022;166:104855 View
  33. Abd-alrazaq A, Alhuwail D, Schneider J, Toro C, Ahmed A, Alzubaidi M, Alajlani M, Househ M. The performance of artificial intelligence-driven technologies in diagnosing mental disorders: an umbrella review. npj Digital Medicine 2022;5(1) View
  34. He J, Yang T. In the era of long COVID, can we seek new techniques for better rehabilitation?. Chronic Diseases and Translational Medicine 2022;8(3):149 View
  35. Dron L, Kalatharan V, Gupta A, Haggstrom J, Zariffa N, Morris A, Arora P, Park J. Data capture and sharing in the COVID-19 pandemic: a cause for concern. The Lancet Digital Health 2022;4(10):e748 View
  36. Hasan M, Bath P, Marincowitz C, Sutton L, Pilbery R, Hopfgartner F, Mazumdar S, Campbell R, Stone T, Thomas B, Bell F, Turner J, Biggs K, Petrie J, Goodacre S. Pre-hospital prediction of adverse outcomes in patients with suspected COVID-19: Development, application and comparison of machine learning and deep learning methods. Computers in Biology and Medicine 2022;151:106024 View
  37. Gao Y, Xiong X, Jiao X, Yu Y, Chi J, Zhang W, Chen L, Li S, Gao Q. PRCTC: a machine learning model for prediction of response to corticosteroid therapy in COVID-19 patients. Aging 2022;14(1):54 View
  38. ÜSTÜNDAĞLI ERTEN E. COVID19 SÜRECİNDE DERGİPARK SİSTEMİNDE YAYINLANAN İŞLETME ODAĞINDAKİ ÇALIŞMALARIN NİTELİKSEL DEĞERLENDİRMESİ. Beykoz Akademi Dergisi 2022:157 View
  39. Ramón A, Zaragozá M, Torres A, Cascón J, Blasco P, Milara J, Mateo J. Application of Machine Learning in Hospitalized Patients with Severe COVID-19 Treated with Tocilizumab. Journal of Clinical Medicine 2022;11(16):4729 View
  40. Hasan M, Bath P, Marincowitz C, Sutton L, Pilbery R, Hopfgartner F, Mazumdar S, Campbell R, Stone T, Benjamin T, Bell F, Turner J, Biggs K, Petrie J, Goodacre S. Pre-Hospital Prediction of Adverse Outcomes in Patients with Suspected COVID-19: Development, Application and Comparison of Machine Learning and Deep Learning Methods. SSRN Electronic Journal 2022 View
  41. Suárez Fernández C, Armario P, Cepeda J, López Carmona M, Miramontes González J, Said-Criado I. Recommendations for the care of patients with cardiovascular disease in health emergency situations: a call to action. Current Medical Research and Opinion 2023;39(6):827 View
  42. Mano L, Torres A, Morales A, Cruz C, Cardoso F, Alves S, Faria C, Lanzillotti R, Cerceau R, da Costa R, Figueiredo K, Werneck V. Machine Learning Applied to COVID-19: A Review of the Initial Pandemic Period. International Journal of Computational Intelligence Systems 2023;16(1) View
  43. Mulenga C, Kaonga P, Hamoonga R, Mazaba M, Chabala F, Musonda P, Ramadas A. Predicting Mortality in Hospitalized COVID-19 Patients in Zambia: An Application of Machine Learning. Global Health 2023;2023:1 View
  44. Chafai N, Bonizzi L, Botti S, Badaoui B. Emerging applications of machine learning in genomic medicine and healthcare. Critical Reviews in Clinical Laboratory Sciences 2024;61(2):140 View
  45. Burnazovic E, Yee A, Levy J, Gore G, Abbasgholizadeh Rahimi S. Application of Artificial intelligence in COVID-19-related geriatric care: A scoping review. Archives of Gerontology and Geriatrics 2024;116:105129 View
  46. Shi Y, Qin Y, Zheng Z, Wang P, Liu J. Risk Factor Analysis and Multiple Predictive Machine Learning Models for Mortality in COVID-19: A Multicenter and Multi-Ethnic Cohort Study. The Journal of Emergency Medicine 2023;65(6):e584 View
  47. Liu L, Song W, Patil N, Sainlaire M, Jasuja R, Dykes P. Predicting COVID-19 severity: Challenges in reproducibility and deployment of machine learning methods. International Journal of Medical Informatics 2023;179:105210 View
  48. Ghosh A, Larrondo-Petrie M, Pavlovic M. Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches. Information 2023;14(12):665 View
  49. Melo D, Vilela Junior D, Rodrigues L, Pereira K. Aplicações da inteligência artificial no combate à COVID-19. Revista Brasileira de Inovação 2023;22:1 View
  50. Hien N, Tsai F, Chang Y, Burton W, Phuc P, Nguyen P, Harnod D, Lam C, Lu T, Chen C, Hsu M, Lu C, Huang C, Yang H, Hsu J. Unveiling the future of COVID-19 patient care: groundbreaking prediction models for severe outcomes or mortality in hospitalized cases. Frontiers in Medicine 2024;10 View
  51. Tukur M, Saad G, AlShagathrh F, Househ M, Agus M. Telehealth interventions during COVID-19 pandemic: a scoping review of applications, challenges, privacy and security issues. BMJ Health & Care Informatics 2023;30(1):e100676 View
  52. Yilmaz G, Sezer S, Bastug A, Singh V, Gopalan R, Aydos O, Ozturk B, Gokcinar D, Kamen A, Gramz J, Bodur H, Akbiyik F. Concordance and generalization of an AI algorithm with real-world clinical data in the pre-omicron and omicron era. Heliyon 2024;10(3):e25410 View
  53. Abd-alrazaq A, Nashwan A, Shah Z, Abujaber A, Alhuwail D, Schneider J, AlSaad R, Ali H, Alomoush W, Ahmed A, Aziz S. Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study. JMIR Formative Research 2024;8:e49411 View
  54. Kuziemsky C, Chrimes D, Minshall S, Mannerow M, Lau F. AI Quality Standards in Health Care: Rapid Umbrella Review. Journal of Medical Internet Research 2024;26:e54705 View
  55. Golos A, Guntuku S, Buttenheim A. “Do not inject our babies”: a social listening analysis of public opinion about authorizing pediatric COVID-19 vaccines. Health Affairs Scholar 2024;2(7) View
  56. Gariti A. Do androids dream of informed consent? The need to understand the ethical implications of experimentation on simulated beings. Monash Bioethics Review 2024 View
  57. Alberts F, Berke O, Rocha L, Keay S, Maboni G, Poljak Z. Predicting host species susceptibility to influenza viruses and coronaviruses using genome data and machine learning: a scoping review. Frontiers in Veterinary Science 2024;11 View

Books/Policy Documents

  1. Dallas I, Vrahatis A, Tasoulis S, Plagianakos V. Computational Intelligence Methods for Bioinformatics and Biostatistics. View
  2. Kolmogorov D, Meniailov I. Integrated Computer Technologies in Mechanical Engineering - 2021. View
  3. Bazilevych K, Butkevych M, Padalko H. Smart Technologies in Urban Engineering. View
  4. Lefèvre T, Colineaux H, Morgand C, Tournois L, Delpierre C. Artificial Intelligence in Covid-19. View
  5. Pike A, Benkli B, Gilani S, Hirani S. Substance Use and Addiction Research. View
  6. Mondal H, Mondal S, Singla R. Artificial Intelligence in Medical Virology. View
  7. Hosseini-Nezhad P, Hosseini-Nezhad S, Hosseini-Nezhad A. Biopolitics and Shock Economy of COVID-19. View
  8. El-Sherif D, Ahmed A, Sharif A, Elzarif M, Abouzid M. The COVID-19 Aftermath. View