Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts

A survey on deep learning in medical image analysis

Litjens, G., Kooi, T., Bejnordi, B. E., Setio, A. A. A., Ciompi, F., Ghafoorian, M., van der Laak, J. A. W. M., van Ginneken, B., & Sánchez, C. I. (2017) · Medical Image Analysis · doi:10.1016/j.media.2017.07.005 · Cited by 15,332

Untitled work

(2016) · Cited by 11,679

Identity mappings in deep residual networks

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46493-0_38 · Cited by 10,741

Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR

Corman, V. M., Landt, O., Kaiser, M., Molenkamp, R., Meijer, A., Chu, D. K. W., Bleicker, T., Brünink, S., Schneider, J. A., Schmidt, M. L., et al. (2020) · Eurosurveillance · doi:10.2807/1560-7917.es.2020.25.3.2000045 · Cited by 7,266

Federated Machine Learning: Concept and Applications

Yang, Q., Liu, Y., Chen, T., & Tong, Y. (2019) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3298981 · Cited by 6,322

Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)

Adadi, A., & Berrada, M. (2018) · IEEE Access · doi:10.1109/access.2018.2870052 · Cited by 6,294

World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19)

Sohrabi, C., Alsafi, Z., O’Neill, N., Khan, M., Kerwan, A., Al‐Jabir, A., Iosifidis, C., & Agha, R. (2020) · International Journal of Surgery · doi:10.1016/j.ijsu.2020.02.034 · Cited by 6,269

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the challenges

Lai, C.-C., Shih, T.-P., Ko, W.-C., Tang, H.-J., & Hsueh, P.-R. (2020) · International Journal of Antimicrobial Agents · doi:10.1016/j.ijantimicag.2020.105924 · Cited by 6,068

Deep learning in medical image analysis

Shen, D., Wu, G., & Suk, H.-I. (2017) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-071516-044442 · Cited by 4,968

The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak

Chinazzi, M., Davis, J. T., Ajelli, M., Gioannini, C., Litvinova, M., Merler, S., Pastore y Piontti, A., Mu, K., Rossi, L., Sun, K., et al. (2020) · Science · doi:10.1126/science.aba9757 · Cited by 3,694

Federated learning for smart healthcare: A survey

Nguyen, D. C., Pham, Q.-V., Pathirana, P. N., Ding, M., Seneviratne, A., Lin, Z., Dobre, O., & Hwang, W.-J. (2023) · ACM Computing Surveys · doi:10.1145/3501296 · Cited by 827

Spatial analysis and GIS in the study of COVID-19. A review

Franch-Pardo, I., Napoletano, B. M., Vergés, F. A. R., & Billa, L. (2020) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2020.140033 · Cited by 669

Metaverse for Healthcare: A Survey on Potential Applications, Challenges and Future Directions

Chengoden, R., Victor, N., Huynh‐The, T., Yenduri, G., Jhaveri, R. H., Alazab, M., Bhattacharya, S., Hegde, P., Maddikunta, P. K. R., & Gadekallu, T. R. (2023) · IEEE Access · doi:10.1109/access.2023.3241628 · Cited by 569

COVID-19 Patient Health Prediction Using Boosted Random Forest Algorithm

Iwendi, C., Bashir, A. K., Peshkar, A., Sujatha, R., Chatterjee, J. M., Pasupuleti, S., Mishra, R., Pillai, S. K., & Jo, O. (2020) · Frontiers in Public Health · doi:10.3389/fpubh.2020.00357 · Cited by 536

Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey

Bhattacharya, S., Maddikunta, P. K. R., Pham, Q., Gadekallu, T. R., Siva Rama Krishnan, S., Chowdhary, C. L., Alazab, M., & Piran, M. J. (2020) · Sustainable Cities and Society · doi:10.1016/j.scs.2020.102589 · Cited by 495

AI4COVID-19: AI enabled preliminary diagnosis for COVID-19 from cough samples via an app

Imran, A., Posokhova, I., Qureshi, H. N., Masood, U., Riaz, M. S., Ali, K., John, C. N., Hussain, M. I., & Nabeel, M. (2020) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2020.100378 · Cited by 621

Information technology solutions, challenges, and suggestions for tackling the COVID-19 pandemic

He, W., Zhang, Z., & Li, W. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102287 · Cited by 482

Federated Learning for Privacy Preservation in Smart Healthcare Systems: A Comprehensive Survey

Ali, M., Naeem, F., Tariq, M., & Kaddoum, G. (2023) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3181823 · Cited by 366

Artificial intelligence in environmental monitoring: Advancements, challenges, and future directions

Olawade, D. B., Wada, O. Z., Ige, A. O., Egbewole, B. I., Olojo, A. S., & Oladapo, B. I. (2024) · Hygiene and Environmental Health Advances · doi:10.1016/j.heha.2024.100114 · Cited by 418

Big Data for Healthcare Industry 4.0: Applications, challenges and future perspectives

Karataş, M., Erişkin, L., Deveci, M., Pamucar, D. S., & Garg, H. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.116912 · Cited by 308

A Survey on Intelligent Internet of Things: Applications, Security, Privacy, and Future Directions

Aouedi, O., Vu, T.-H., Sacco, A., Nguyen, D. C., Piamrat, K., Marchetto, G., & Pham, Q. (2024) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2024.3430368 · Cited by 345

COVID-19 open source data sets: a comprehensive survey

Shuja, J., Alanazi, E., Alasmary, W., & Alashaikh, A. S. (2020) · Applied Intelligence · doi:10.1007/s10489-020-01862-6 · Cited by 278

Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-Like Epidemics: A Survey

Nguyen, D. C., Ding, M., Pathirana, P. N., & Seneviratne, A. (2021) · IEEE Access · doi:10.1109/access.2021.3093633 · Cited by 286

Review of Big Data Analytics, Artificial Intelligence and Nature-Inspired Computing Models towards Accurate Detection of COVID-19 Pandemic Cases and Contact Tracing

Agbehadji, I. E., Awuzie, B. O., Ngowi, A. B., & Millham, R. C. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17155330 · Cited by 269

Federated learning for secure IoMT-applications in smart healthcare systems: A comprehensive review

Rani, S., Kataria, A., Kumar, S., & Tiwari, P. (2023) · Knowledge-Based Systems · doi:10.1016/j.knosys.2023.110658 · Cited by 228

Applications of artificial intelligence in battling against covid-19: A literature review

Tayarani N., M.-H. (2021) · Chaos, Solitons & Fractals · doi:10.1016/j.chaos.2020.110338 · Cited by 210

Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review

Khan, M., Mehran, M. T., Haq, Z. U., Ullah, Z., Naqvi, S. R., Ihsan, M., & Abbas, H. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2021.115695 · Cited by 212

Roles of Innovation Leadership on Using Big Data Analytics to Establish Resilient Healthcare Supply Chains to Combat the COVID-19 Pandemic: A Multimethodological Study

Bag, S., Gupta, S., Choi, T., & Kumar, A. (2021) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2021.3101590 · Cited by 214

IoT in the Wake of COVID-19: A Survey on Contributions, Challenges and Evolution

Ndiaye, M., Oyewobi, S. S., Abu-Mahfouz, A. M. I., Hancke, G. P., Kurien, A. M., & Djouani, K. (2020) · IEEE Access · doi:10.1109/access.2020.3030090 · Cited by 175

Artificial intelligence approaches and mechanisms for big data analytics: a systematic study

Rahmani, A. M., Azhir, E., Ali, S., Mohammadi, M., Ahmed, O. H., Ghafour, M. Y., Ahmed, S. H., & Hosseinzadeh, M. (2021) · PeerJ Computer Science · doi:10.7717/peerj-cs.488 · Cited by 175

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies

Nguyen, C. T., Saputra, Y. M., Huynh, N. V., Nguyen, N.-T., Khoa, T. V., Tuan, B. M., Nguyen, D. N., Hoang, D. T., Vu, T. X., Dutkiewicz, E., et al. (2020) · IEEE Access · doi:10.1109/access.2020.3018140 · Cited by 185

Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review

Comito, C., & Pizzuti, C. (2022) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2022.102286 · Cited by 174

Cough Sound Detection and Diagnosis Using Artificial Intelligence Techniques: Challenges and Opportunities

Alqudaihi, K. S., Aslam, N., Khan, I. U., Almuhaideb, A. M., Alsunaidi, S. J., Ibrahim, N. M., Alhaidari, F. A., Shaikh, F. S., Alsenbel, Y. M., Alalharith, D. M., et al. (2021) · IEEE Access · doi:10.1109/access.2021.3097559 · Cited by 153

Contact tracing apps for the COVID-19 pandemic: a systematic literature review of challenges and future directions for neo-liberal societies

Akinbi, A., Forshaw, M. J., & Blinkhorn, V. (2021) · Health Information Science and Systems · doi:10.1007/s13755-021-00147-7 · Cited by 145

POCOVID-Net: Automatic Detection of COVID-19 From a New Lung Ultrasound Imaging Dataset (POCUS)Preprint

Born, J., Brändle, G., Cossio, M., Disdier, M., Goulet, J., Roulin, J., & Wiedemann, N. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.12084 · Cited by 182

Systematic Review on AI-Blockchain Based E-Healthcare Records Management Systems

Haddad, A., Habaebi, M. H., Islam, M. R., Hasbullah, N. F., & Zabidi, S. A. (2022) · IEEE Access · doi:10.1109/access.2022.3201878 · Cited by 152

A Multivocal Literature Review on Growing Social Engineering Based Cyber-Attacks/Threats During the COVID-19 Pandemic: Challenges and Prospective Solutions

Hijji, M., & Alam, G. (2021) · IEEE Access · doi:10.1109/access.2020.3048839 · Cited by 134

A comprehensive survey on federated learning techniques for healthcare informatics

Dasaradharami Reddy, K., & Gadekallu, T. R. (2023) · Computational Intelligence and Neuroscience · doi:10.1155/2023/8393990 · Cited by 126

The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges

Ahmad, A., Garhwal, S., Ray, S. K., Kumar, G., Malebary, S. J., & Barukab, O. (2020) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-020-09472-8 · Cited by 110

DeepCOVIDNet: An Interpretable Deep Learning Model for Predictive Surveillance of COVID-19 Using Heterogeneous Features and Their Interactions

Ramchandani, A., Fan, C. H., & Mostafavi, A. (2020) · IEEE Access · doi:10.1109/access.2020.3019989 · Cited by 91

The Role Of Technology In Era 5.0 In The Development Of Arabic Language In The World Of Education

Keshav, M., Julien, L., & Miezel, J. (2022) · Journal International of Lingua and Technology · doi:10.55849/jiltech.v1i2.85 · Cited by 97

A systematic review on AI/ML approaches against COVID-19 outbreak

Dogan, O., Tiwari, S., Jabbar, M. A., & Guggari, S. (2021) · Complex & Intelligent Systems · doi:10.1007/s40747-021-00424-8 · Cited by 87

Internet‐of‐medical‐things integrated point‐of‐care biosensing devices for infectious diseases: Toward better preparedness for futuristic pandemics

Parihar, A., Yadav, S., Sadique, M. A., Ranjan, P., Kumar, N., Singhal, A., Khare, V., Khan, R., Sathish, N., & Srivastava, A. K. (2023) · Bioengineering & Translational Medicine · doi:10.1002/btm2.10481 · Cited by 82

Artificial intelligence national strategy in a developing country

Demaidi, M. N. (2025) · AI & SOCIETY · doi:10.1007/s00146-023-01779-x · Cited by 82

Explainable Machine Learning for Early Assessment of COVID-19 Risk Prediction in Emergency Departments

Casiraghi, E., Malchiodi, D., Trucco, G., Frasca, M., Cappelletti, L., Fontana, T., Esposito, A. A., Avola, E., Jachetti, A., Reese, J., et al. (2020) · IEEE Access · doi:10.1109/access.2020.3034032 · Cited by 81

A Blockchain-Based Artificial Intelligence-Empowered Contagious Pandemic Situation Supervision Scheme Using Internet of Drone Things

Islam, A., Rahim, T., Masuduzzaman, M., & Shin, S. Y. (2021) · IEEE Wireless Communications · doi:10.1109/mwc.001.2000429 · Cited by 79

Machine learning research towards combating COVID-19: Virus detection, spread prevention, and medical assistance

Shahid, O., Nasajpour, M., Pouriyeh, S., Parizi, R. M., Han, M., Valero, M., Li, F., Aledhari, M., & Sheng, Q. Z. (2021) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2021.103751 · Cited by 80

Blockchain and COVID-19 pandemic: applications and challenges

Ahmad, R. W., Salah, K., Jayaraman, R., Yaqoob, I., Ellahham, S. H., & Omar, M. (2023) · Cluster Computing · doi:10.1007/s10586-023-04009-7 · Cited by 81

Novel Coronavirus Cough Database: NoCoCoDa

Cohen-McFarlane, M., Goubran, R., & Knoefel, F. (2020) · IEEE Access · doi:10.1109/access.2020.3018028 · Cited by 78

Prediction of the final size for COVID-19 epidemic using machine learning: A case study of Egypt

Amar, L. A., Taha, A. A., & Mohamed, M. Y. (2020) · Infectious Disease Modelling · doi:10.1016/j.idm.2020.08.008 · Cited by 69

Paper-based analytical devices for virus detection: Recent strategies for current and future pandemics

Özer, T., & Henry, C. S. (2021) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2021.116424 · Cited by 68

Detecting COVID-19-Related Fake News Using Feature Extraction

Khan, S. A., Hakak, S., Deepa, N., Prabadevi, B., Dev, K., & Treľová, S. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2021.788074 · Cited by 63

Management of Smart and Sustainable Cities in the Post-COVID-19 Era: Lessons and Implications

Striełkowski, W., Zenchenko, S. V., Tarasova, A., & Radyukova, Y. (2022) · Sustainability · doi:10.3390/su14127267 · Cited by 63

Diagnosis of COVID-19 Using Machine Learning and Deep Learning: A Review

Mondal, M. R. H., Bharati, S., & Podder, P. (2021) · Current Medical Imaging Formerly Current Medical Imaging Reviews · doi:10.2174/1573405617666210713113439 · Cited by 68

COVID-19 in the Age of Artificial Intelligence: A Comprehensive Review

Rasheed, J., Jamıl, A., Hameed, A. A., Al-Turjman, F. M., & Rasheed, A. (2021) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-021-00431-w · Cited by 61

Paper-Based Biosensors for COVID-19: A Review of Innovative Tools for Controlling the Pandemic

Pinheiro, T., Cardoso, A. R. A., Sousa, C. E. A., Marques, A. C., Tavares, A. P. M., Matos, A. M., Cruz, M. T., Moreira, F. T. C., Martins, R., Fortunato, E. M. C., et al. (2021) · ACS Omega · doi:10.1021/acsomega.1c04012 · Cited by 62

15 years of Big Data: a systematic literature review

Tosi, D., Kokaj, R., & Roccetti, M. (2024) · Journal Of Big Data · doi:10.1186/s40537-024-00914-9 · Cited by 59

Artificial intelligence in smart drug delivery systems: a step toward personalized medicine

Panchpuri, M., Painuli, R., & Kumar, C. (2025) · RSC Pharmaceutics · doi:10.1039/d5pm00089k · Cited by 66

COVID-19 health analysis and prediction using machine learning algorithms for Mexico and Brazil patients

Iwendi, C., Huescas, C. G. Y., Chakraborty, C., & Mohan, S. (2022) · Journal of Experimental & Theoretical Artificial Intelligence · doi:10.1080/0952813x.2022.2058097 · Cited by 58

Public Covid-19 X-ray datasets and their impact on model bias – A systematic review of a significant problem

Garcia Santa Cruz, B., Bossa, M. N., Sölter, J., & Husch, A. D. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102225 · Cited by 89

The Role of Internet of Things to Control the Outbreak of COVID-19 Pandemic

Castiglione, A., Umer, M., Sadiq, S., Obaidat, M. S., & Vijayakumar, P. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3070306 · Cited by 57

Artificial Intelligence and Blockchain Enabled Smart Healthcare System for Monitoring and Detection of COVID-19 in Biomedical Images

Ahmed, I., Chehri, A., & Jeon, G. (2023) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2023.3294333 · Cited by 58

Artificial Intelligence and COVID-19: A Systematic umbrella review and roads ahead

Adadi, A., Lahmer, M., & Nasiri, S. (2021) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2021.07.010 · Cited by 59

COVID-19 Diagnostic Methods and Detection Techniques

Rong, G., Zheng, Y., Chen, Y., Zhang, Y., Zhu, P., & Sawan, M. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-822548-6.00080-7 · Cited by 57

A Comprehensive Study of Artificial Intelligence and Machine Learning Approaches in Confronting the Coronavirus (COVID-19) Pandemic

Rahman, M. M., Khatun, F., Uzzaman, A., Sami, S. I., Bhuiyan, M. A.-A., & Kiong, T. S. (2021) · International Journal of Health Services · doi:10.1177/00207314211017469 · Cited by 59

Bridging healthcare gaps: a scoping review on the role of artificial intelligence, deep learning, and large language models in alleviating problems in medical deserts

Strika, Z., Petković, K., Likić, R., & Batenburg, R. S. (2024) · Postgraduate Medical Journal · doi:10.1093/postmj/qgae122 · Cited by 63

The Role of Artificial Intelligence Driven 5G Networks in COVID-19 Outbreak: Opportunities, Challenges, and Future Outlook

Abubakar, A. I., Omeke, K. G., Öztürk, M., Hussain, S., & Imran, M. A. (2020) · Frontiers in Communications and Networks · doi:10.3389/frcmn.2020.575065 · Cited by 55

Pandemic Analytics: How Countries are Leveraging Big Data Analytics and Artificial Intelligence to Fight COVID-19?

Mehta, N. A., & Shukla, S. (2021) · SN Computer Science · doi:10.1007/s42979-021-00923-y · Cited by 57

Emerging Technologies for COVID‐19

Anand, R., Sindhwani, N., Saini, A., & Shubham (2021) · doi:10.1002/9781119769088.ch9 · Cited by 53

A gradient boosting machine learning approach in modeling the impact of temperature and humidity on the transmission rate of COVID-19 in India

Shrivastav, L. K., & Jha, S. K. (2020) · Applied Intelligence · doi:10.1007/s10489-020-01997-6 · Cited by 52

The medical and societal impact of big data analytics and artificial intelligence applications in combating pandemics: A review focused on Covid-19

Galetsi⁠, P., Katsaliaki, K., & Kumar, S. (2022) · Social Science & Medicine · doi:10.1016/j.socscimed.2022.114973 · Cited by 55

Overview of current state of research on the application of artificial intelligence techniques for COVID-19

Kumar, V., Singh, D., Kaur, M., & Damaševičius, R. (2021) · PeerJ Computer Science · doi:10.7717/peerj-cs.564 · Cited by 50

Sociological modeling of smart city with the implementation of UN sustainable development goals

Kolesnichenko, O., Mazelis, L., Sotnik, A., Yakovleva, D., Амелькин, С. А., Grigorevsky, I., & Kolesnichenko, Y. (2021) · Sustainability Science · doi:10.1007/s11625-020-00889-5 · Cited by 62

Diagnosing COVID-19 using artificial intelligence: a comprehensive review

Khanna, V. V., Chadaga, K., Sampathila, N., Prabhu, S., Chadaga, R., & Umakanth, S. (2022) · Network Modeling Analysis in Health Informatics and Bioinformatics · doi:10.1007/s13721-022-00367-1 · Cited by 52

Sustainable, technological, and innovative challenges post Covid-19 in health, economy, and education sectors

Bortoló, G. M., Valdés, J. Á., & Nicolás-Sans, R. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.122424 · Cited by 48

Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches

Ghosh, A., Larrondo-Petrie, M. M., & Pavlović, M. D. (2023) · Information · doi:10.3390/info14120665 · Cited by 51

Deep Learning–Driven Automated Detection of COVID-19 from Radiography Images: a Comparative Analysis

Rahman, S., Sarker, S. C., Miraj, M. A. A., Nihal, R. A., Haque, A. K. M. N., & Noman, A. A. (2021) · Cognitive Computation · doi:10.1007/s12559-020-09779-5 · Cited by 50

The role of contemporary digital tools and technologies in COVID‐19 crisis: An exploratory analysis

Subramanian, M., Kogilavani, S. V., Hatamleh, W. A., Alnuaim, A. A., Abdelhady, M., & Easwaramoorthy, S. V. (2021) · Expert Systems · doi:10.1111/exsy.12834 · Cited by 52

Turning Crisis into Opportunities: How a Firm Can Enrich Its Business Operations Using Artificial Intelligence and Big Data during COVID-19

Chen, Y., & Biswas, M. I. (2021) · Sustainability · doi:10.3390/su132212656 · Cited by 47

Artificial intelligence for COVID-19: battling the pandemic with computational intelligence

Xu, Z., Su, C., Xiao, Y., & Wang, F. (2021) · Intelligent Medicine · doi:10.1016/j.imed.2021.09.001 · Cited by 48

Using artificial intelligence technology to fight COVID-19: a review

Peng, Y., Liu, E., Peng, S., Chen, Q., Li, D., & Lian, D. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-021-10106-z · Cited by 47

An Incentive Based Approach for COVID-19 planning using Blockchain Technology

Manoj, M., Srivastava, G., Somayaji, S. R. K., Gadekallu, T. R., Maddikunta, P. K. R., & Bhattacharya, S. (2020) · IEEE Globecom Workshops (GC Wkshps) · doi:10.1109/gcwkshps50303.2020.9367469 · Cited by 49

Covid19 Unknown Risks—Using AI for Disaster Recovery

Khatib, M. M. E., Beshwari, F., Beshwari, M., Beshwari, A., Alzoubi, H. M., & Alshurideh, M. T. (2023) · Studies in computational intelligence · doi:10.1007/978-3-031-12382-5_116 · Cited by 57

Digital epidemiology: harnessing big data for early detection and monitoring of viral outbreaks

Fallatah, D. I., & Adekola, H. A. (2024) · Infection Prevention in Practice · doi:10.1016/j.infpip.2024.100382 · Cited by 50

Review on the COVID-19 pandemic prevention and control system based on AI

Yi, J., Zhang, H., Mao, J., Chen, Y., Zhong, H., & Wang, Y. (2022) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2022.105184 · Cited by 50

Overview of COVID-19 Disease: Virology, Epidemiology, Prevention Diagnosis, Treatment, and Vaccines

Salahshoori, I., Mobaraki-Asl, N., Seyfaee, A., Nasirabad, N. M., Dehghan, Z., Faraji, M., Ganjkhani, M., Babapoor, A., Shadmehr, S., & Hamrang, A. (2021) · Biologics · doi:10.3390/biologics1010002 · Cited by 46

Update in COVID-19 in the intensive care unit from the 2020 HELLENIC Athens International symposium

Rello, J., Belliato, M., Dimopoulos, M. A., Giamarellos‐Bourboulis, E. J., Jaksic, V., Martín‐Loeches, I., Mporas, I., Pelosi, P. P., Poulakou, G., Pournaras, S., et al. (2020) · Anaesthesia Critical Care & Pain Medicine · doi:10.1016/j.accpm.2020.10.008 · Cited by 41

Role of deep learning in early detection of COVID-19: Scoping review

Alzubaidi, M. S., Zubaydi, H. D., Bin-Salem, A. A., Abd-Alrazaq, A. A., Ahmed, A., & Househ, M. S. (2021) · Computer Methods and Programs in Biomedicine Update · doi:10.1016/j.cmpbup.2021.100025 · Cited by 41

COVID-19 Severity Prediction Using Enhanced Whale with Salp Swarm Feature Classification

Budimirović, N., Prabhu, E., Antonijević, M., Zivkovic, M. Z., Bačanin, N., Strumberger, I., & Venkatachalam, K. (2022) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2022.023418 · Cited by 42

Enhanced Multi-Model Deep Learning for Rapid and Precise Diagnosis of Pulmonary Diseases Using Chest X-Ray Imaging

Kumar, R., Pan, C., Lin, Y., Shiue, Y., Chung, T.-S., & Janesha, U. G. S. (2025) · Diagnostics · doi:10.3390/diagnostics15030248 · Cited by 46

Enabling and Emerging Technologies for Social Distancing: A Comprehensive Survey

Ct, N., Ym, S., Nv, H., Nguyen, N.-T., Tv, K., Bm, T., Nguyen, D., Dt, H., Vu, T. X., Dutkiewicz, E., et al. (2020) · Europe PMC (PubMed Central) · Cited by 39

COVID‐19: A multiwave SIR‐based model for learning waves

Perakis, G., Singhvi, D., Lami, O. S., & Thayaparan, L. (2022) · Production and Operations Management · doi:10.1111/poms.13681 · Cited by 37

A bibliometric analysis of the advance of artificial intelligence in medicine

Lin, M., Lin, L., Lin, L., Lin, Z., & Yan, X. (2025) · Frontiers in Medicine · doi:10.3389/fmed.2025.1504428 · Cited by 36

Artificial intelligence in the COVID-19 pandemic: balancing benefits and ethical challenges in China’s response

Ding, X., Shang, B., Xie, C., Xin, J., & Yu, F. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-04564-x · Cited by 44

A novel perceptual two layer image fusion using deep learning for imbalanced COVID-19 dataset

Elzeki, O. M., Elfattah, M. A., Salem, H., Hassanien, A. E., & Shams, M. Y. (2021) · PeerJ Computer Science · doi:10.7717/peerj-cs.364 · Cited by 36

Big Data COVID-19 Systematic Literature Review: Pandemic Crisis

Haafza, L. A., Awan, M. J., Abid, A., Yasin, A., Nobanee, H., & Farooq, M. S. (2021) · Electronics · doi:10.3390/electronics10243125 · Cited by 36

A Deep Learning BiLSTM Encoding-Decoding Model for COVID-19 Pandemic Spread Forecasting

Shahin, A. I., & Almotairi, S. (2021) · Fractal and Fractional · doi:10.3390/fractalfract5040175 · Cited by 34

An innovative big data framework for exploring the impact on decision-making in the European Mediterranean healthcare sector

Samad, M. E., Nemar, S. E., Sakka, G., & El-Chaarani, H. (2022) · EuroMed Journal of Business · doi:10.1108/emjb-11-2021-0168 · Cited by 34

Medical Imaging with Deep Learning for COVID- 19 Diagnosis: A Comprehensive ReviewPreprint

Bharati, S., Podder, P., Mondal, M. R. H., & Prasath, V. B. S. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.09602 · Cited by 50

Impact of Artificial Intelligence on COVID-19 Pandemic: A Survey of Image Processing, Tracking of Disease, Prediction of Outcomes, and Computational Medicine

Almotairi, K. H., Hussein, A. M., Abualigah, L., Abujayyab, S. K. M., Mahmoud, E. H., Ghanem, B. O., & Gandomi, A. H. (2023) · Big Data and Cognitive Computing · doi:10.3390/bdcc7010011 · Cited by 37

COVID-19-The Role of Artificial Intelligence, Machine Learning, and Deep Learning: A Newfangled

Vinod, D. N., & Prabaharan, S. R. S. (2023) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-023-09882-4 · Cited by 31

Federated Learning for Human Activity Recognition: Overview, Advances, and Challenges

Aouedi, O., Sacco, A., Khan, L. U., Nguyen, D. C., & Guizani, M. (2024) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2024.3484228 · Cited by 42

Towards Providing Effective Data-Driven Responses to Predict the Covid-19 in São Paulo and Brazil

Amaral, F., Casaca, W. C. D. O., Oishi, C. M., & Cuminato, J. A. (2021) · Sensors · doi:10.3390/s21020540 · Cited by 30

AI for COVID-19 Detection from Radiographs: Incisive Analysis of State of the Art Techniques, Key Challenges and Future Directions

Karthik, R., Menaka, R., Hariharan, M., & Kathiresan, G. S. (2021) · IRBM · doi:10.1016/j.irbm.2021.07.002 · Cited by 30

Battling COVID-19 using machine learning: A review

Chadaga, K., Prabhu, S., Vivekananda Bhat, K., Niranjana, S., & Umakanth, S. (2021) · Cogent Engineering · doi:10.1080/23311916.2021.1958666 · Cited by 30

BOSS : A new QoS aware blockchain assisted framework for secure and smart healthcare as a service

Singh, P., Kaur, R., Dhiman, G., & Bojja, G. R. (2021) · Expert Systems · doi:10.1111/exsy.12838 · Cited by 30

Ética e Inteligência Artificial

García, A. C. B. (2020) · Computação Brasil. · doi:10.5753/compbr.2020.43.1791 · Cited by 29

Application of Artificial Intelligence and Big Data for Fighting COVID-19 Pandemic

Awotunde, J. B., Folorunso, S. O., Chakraborty, C., Bhoi, A. K., & Ajamu, G. J. (2022) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-3-030-87019-5_1 · Cited by 30

Identification of COVID-19 Spreaders Using Multiplex Networks Approach

Montes-Orozco, E., Mora-Gutiérrez, R. A., de-los-Cobos-Silva, S. G., Rincón-García, E. A., Torres-Cockrell, G.-S., Juárez‐Gómez, J., Obregón-Quintana, B., Lara-Velázquez, P., & Andrade, M. Á. G. (2020) · IEEE Access · doi:10.1109/access.2020.3007726 · Cited by 29

Big data driven COVID-19 pandemic crisis management: Potential approach for global health

Lv, Y., Ma, C., Li, X., & Wu, M. (2021) · Archives of Medical Science · doi:10.5114/aoms/133522 · Cited by 28

Artificial Intelligence and Big Data Solutions for COVID-19

Rayan, R. Α., Zafar, I., & Tsagkaris, C. (2021) · Algorithms for intelligent systems · doi:10.1007/978-981-16-1574-0_6 · Cited by 7

Application of AI Techniques for COVID-19 in IoT and Big Data Era: A Survey

Hussain, A. A., Dawood, B. A., & Al-Turjman, F. M. (2021) · Studies in computational intelligence · doi:10.1007/978-3-030-60188-1_9 · Cited by 13

Artificial Intelligence (AI) and Big Data Analytics for the COVID-19 Pandemic

Pandit, P., Krishnamurthy, K. N., & Bakshi, B. (2021) · Springer eBooks · doi:10.1007/978-3-030-79753-9_1 · Cited by 2

Artificial intelligence and big data for COVID-19 and social distancing

Pham, Q., Nguyen, D. C., Huynh‐The, T., Pathirana, P. N., & Hwang, W. (2022) · Institution of Engineering and Technology eBooks · doi:10.1049/pbte104e_ch5

Analysis of Convolution neural network algorithms for Classification of Covid-19 Computed Tomography Images

Roopa, V., Shyni, E., & Malar, A. C. J. (2022) · Ecology Environment and Conservation · doi:10.53550/eec.2022.v28i06s.068