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

Artificial Intelligence Approach to Predict the COVID-19 Patient’s Recovery

Salama, A., Darwsih, A., & Hassanien, A. E. (2021) · Studies in systems, decision and control · doi:10.1007/978-3-030-63307-3_8 · Cited by 24

A Machine Learning Application for Raising WASH Awareness in the Times of COVID-19 Pandemic (Preprint)Preprint

Pandey, R., Gautam, V., Pal, R., Bandhey, H., Dhingra, L. S., Sharma, H., Jain, C., Bhagat, K., Arushi, A., Patel, L., et al. (2020) · doi:10.2196/preprints.25320 · Cited by 24

COVID-MobileXpert: On-Device COVID-19 Patient Triage and Follow-up using Chest X-raysPreprint

Li, X. S., Li, C., & Zhu, D. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.03042 · Cited by 24

Machine Learning for Prediction of Patients on Hemodialysis with an Undetected SARS-CoV-2 Infection

Monaghan, C. K., Larkin, J. W., Chaudhuri, S., Han, H., Jiao, Y., Bermudez, K. M., Weinhandl, E. D., Dahne-Steuber, I. A., Belmonte, K., Neri, L., et al. (2021) · Kidney360 · doi:10.34067/kid.0003802020 · Cited by 24

A sinusoid size ring structure Quantum Evolutionary Algorithm

Tayarani-N, M. H., & Akbarzadeh-T, M.-R. (2008) · IEEE Conference on Cybernetics and Intelligent Systems · doi:10.1109/iccis.2008.4670952 · Cited by 23

Evaluating the Traditional Chinese Medicine (TCM) Officially Recommended in China for COVID-19 Using Ontology-Based Side-Effect Prediction Framework (OSPF) and Deep LearningPreprint

Wang, Z., Li, L., Yan, J., et al. (2020) · Preprints.org · doi:10.20944/preprints202002.0230.v1 · Cited by 23

First-principles machine learning modelling of COVID-19Preprint

Magri, L., & Doan, N. A. K. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.09478 · Cited by 23

Outbreak prediction of covid-19 in most susceptible countries

Yadav, D., Maheshwari, H. S., & Chandra, U. (2020) · DOAJ (DOAJ: Directory of Open Access Journals) · doi:10.22034/gjesm.2019.06.si.02 · Cited by 23

Predicting the COVID-19 positive cases in India with concern to Lockdown by using Mathematical and Machine Learning based ModelsPreprint

Pasayat, A. K., Pati, S. N., & Maharana, A. (2020) · medRxiv · doi:10.1101/2020.05.16.20104133 · Cited by 23

Automated Detection of COVID-19 from CT Scans using Convolutional Neural Networks

Lokwani, R., Gaikwad, A., Kulkarni, V., Pant, A., & Kharat, A. T. (2021) · International Conference on Pattern Recognition Applications and Methods · doi:10.5220/0010293605650570 · Cited by 23

Computational predictions for protein sequences of COVID-19 virus via machine learning algorithms

Alkady, W., Zanaty, M. S., & Afify, H. M. (2021) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-021-02412-z · Cited by 23

3D Tomographic Pattern Synthesis for Enhancing the Quantification of COVID-19Preprint

Liu, S., Georgescu, B., Xu, Z., Yoo, Y., Chabin, G., Chaganti, S., Grbić, S., Piat, S., Teixeira, B., Balachandran, A., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.01903 · Cited by 22

Data Analytics: COVID-19 Prediction Using Multimodal DataPreprint

Mahalle, P. N., Sable, N. P., Mahalle, N. P., et al. (2020) · Preprints.org · doi:10.20944/preprints202004.0257.v2 · Cited by 22

Forecasting Covid-19 dynamics in Brazil: a data driven approachPreprint

Pereira, I. G., Guerin, J. M., Silva, A., et al. (2020) · medRxiv · doi:10.1101/2020.05.11.20098392 · Cited by 22

Deep convolutional approaches for the analysis of Covid-19 using chest X-Ray images from portable devicesPreprint

de Moura, J., Ramos, L., Vidal, P. L., et al. (2020) · medRxiv · doi:10.1101/2020.06.18.20134593 · Cited by 22

A Survey on Applications of Artificial Intelligence in Fighting Against COVID-19Preprint

Chen, J., Li, K., Zhang, Z., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.02202 · Cited by 22

Toward Preparing a Knowledge Base to Explore Potential Drugs and Biomedical Entities Related to COVID-19: Automated Computational Approach

Khan, J. Y., Khondaker, M. T. I., Hoque, I. T., Al-Absi, H. R. H., Rahman, M. S., Guler, R., Alam, T., & Rahman, M. S. (2020) · JMIR Medical Informatics · doi:10.2196/21648 · Cited by 22

Similarity maps and pairwise predictions for transmission dynamics of COVID-19 with neural networks

Hartono, P. (2020) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2020.100386 · Cited by 22

Machine learning prediction for mortality of patients diagnosed with COVID-19: a nationwide Korean cohort studyPreprint

An, C., Lim, H., Kim, D. W., Chang, J. H., Choi, Y. J., & Kim, S. W. (2020) · doi:10.21203/rs.3.rs-36458/v1 · Cited by 22

An Early Study on Intelligent Analysis of Speech under COVID-19: Severity, Sleep Quality, Fatigue, and AnxietyPreprint

Han, J., Qian, K., Song, M., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.00096 · Cited by 22

Innovative use of artificial intelligence and digital communication in acute stroke pathway in response to COVID-19

Nagaratnam, K., Harston, G., Floßmann, E., Canavan, C., Geraldes, R. C., & Edwards, C. (2020) · Future Healthcare Journal · doi:10.7861/fhj.2020-0034 · Cited by 21

Power of Artificial Intelligence to Diagnose and Prevent Further COVID-19 Outbreak: A Short CommunicationPreprint

Jibril, M. L., & Sharif, U. S. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.12463 · Cited by 21

Coronavirus: Comparing COVID-19, SARS and MERS in the eyes of AIPreprint

Tahir, A., Qiblawey, Y., Khandakar, A. A., Rahman, T., Khurshid, U., Musharavati, F., Serkan Kiranyaz, B., & Chowdhury, M. E. H. (2020) · arXiv (Cornell University) · Cited by 21

Chest X-ray classification using Deep learning for automated COVID-19 screeningPreprint

Shelke, A., Inamdar, M., Shah, V., et al. (2020) · medRxiv · doi:10.1101/2020.06.21.20136598 · Cited by 21

Pollution, Economic Growth and COVID-19 Deaths in India: Machine Learning EvidencePreprint

Mele, M., & Magazzino, C. (2020) · Research Square · doi:10.21203/rs.3.rs-40851/v1 · Cited by 21

Prediction of Patient Management in COVID-19 Using Deep Learning-Based Fully Automated Extraction of Cardiothoracic CT Metrics and Laboratory Findings

Weikert, T., Rapaka, S., Grbić, S., Re, T. J., Chaganti, S., Winkel, D. J., Anastasopoulos, C., Niemann, T., Wiggli, B. J., Bremerich, J., et al. (2021) · Korean Journal of Radiology · doi:10.3348/kjr.2020.0994 · Cited by 21

A cellular structure and diversity preserving operator in Quantum Evolutionary Algorithms

N., M. H. T., & T., M. R. A. (2008) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2008.4631156 · Cited by 20

Countries are Clustered but Number of Tests is not Vital to Predict Global COVID-19 Confirmed Cases: A Machine Learning ApproachPreprint

Khan, M. H. R., & Hossain, A. (2020) · medRxiv · doi:10.1101/2020.04.24.20078238 · Cited by 20

Interpretable Artificial Intelligence for COVID-19 Diagnosis from Chest CT Reveals Specificity of Ground-Glass OpacitiesPreprint

Warman, A., Warman, P. I., Sharma, A., Parikh, P., Warman, R., Viswanadhan, N., Chen, L., Mohapatra, S., Mohapatra, S. S., & Sapiro, G. (2020) · medRxiv · doi:10.1101/2020.05.16.20103408 · Cited by 20

Can artificial intelligence identify effective COVID‐19 therapies?

Schultz, M. B., Vera, D. L., & Sinclair, D. A. (2020) · EMBO Molecular Medicine · doi:10.15252/emmm.202012817 · Cited by 20

A Review of Automated Diagnosis of COVID-19 Based on Scanning Images

Chen, D., Ji, S., Liu, F., Li, Z., & Zhou, X. (2020) · doi:10.1145/3449301.3449778 · Cited by 20

Artificial Intelligence (AI) Applications for Library Services and Resources in COVID-19 PandemicPreprint

Nawaz, N., Gomes, A. M., & Saldeen, M. A. (2020) · SSRN Electronic Journal · Cited by 20

An aberration detection-based approach for sentinel syndromic surveillance of COVID-19 and other novel influenza-like illnesses

Wen, A., Wang, L., He, H., Liu, S., Fu, S., Sohn, S., Kugel, J. A., Kaggal, V. C., Huang, M. S., Wang, Y., et al. (2020) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2020.103660 · Cited by 20

From Community Acquired Pneumonia to COVID-19: A Deep Learning Based Method for Quantitative Analysis of COVID-19 on thick-section CT ScansPreprint

Li, Z., Zheng, Z., Li, Y., et al. (2020) · medRxiv · doi:10.1101/2020.04.17.20070219 · Cited by 19

Worldwide and Regional Forecasting of Coronavirus (Covid-19) Spread using a Deep Learning ModelPreprint

Direkoğlu, C., & Şah, M. (2020) · medRxiv · doi:10.1101/2020.05.23.20111039 · Cited by 19

4S-DT : Self Supervised Super Sample Decomposition for Transfer learning with application to COVID-19 detectionPreprint

Abbas, A., Abdelsamea, M. M., & Gaber, M. M. (2020) · medRxiv · doi:10.1101/2020.06.22.20137547 · Cited by 19

COVID-19 Lung Infection Segmentation

Elharrouss, O., Subramanian, N., Almaadeed, N., & Al-Maadeed, S. A. (2020) · University of the Future: Re-Imagining Research and Higher Education · doi:10.29117/quarfe.2020.0294 · Cited by 19

COVID-19 detection and disease progression visualization: Deep learning on chest X-rays for classification and coarse localizationPreprint

Zebin, T., Rezvy, S., & Pang, W. (2020) · Research Square · doi:10.21203/rs.3.rs-34534/v1 · Cited by 19

Open Data Resources for Fighting COVID-19Preprint

Álamo, T., Dg, R., Mammarella, M., & Abella, A. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.06111 · Cited by 18

A Novel Strategy for the Development of Vaccines for SARS-CoV‑2 (COVID-19) and Other Viruses Using AI and Viral Shell Disorder

Goh, G. K., Dunker, A. K., Foster, J. A., & Uversky, V. N. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00672 · Cited by 18

Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification with Chest CTPreprint

Sun, L., Mo, Z., Yan, F., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.03264 · Cited by 18

Coronavirus Infectious Disease (COVID-19) Modeling: Evidence of Geographical SignalsPreprint

Keshavarzi, A. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3568425 · Cited by 18

Deep Learning and Holt-Trend Algorithms for predicting COVID-19 pandemicPreprint

Aldhyani, T. H. H., Alrasheed, M., Alqarni, A. A., et al. (2020) · medRxiv · doi:10.1101/2020.06.03.20121590 · Cited by 18

Artificial Intelligence‐Based Clinical Decision Support for COVID‐19–Where Art Thou?

Unberath, M., Ghobadi, K., Levin, S., Hinson, J. S., & Hager, G. D. (2020) · Advanced Intelligent Systems · doi:10.1002/aisy.202000104 · Cited by 18

A Comparative Study on Early Detection of COVID-19 from Chest X-Ray ImagesPreprint

Ahishali, M., Degerli, A., Yamaç, M., Serkan Kiranyaz, B., Chowdhury, M. E. H., Hameed, K., Hamid, T., Mazhar, R., & Gabbouj, M. (2020) · arXiv (Cornell University) · Cited by 18

CCBlock: an effective use of deep learning for automatic diagnosis of COVID-19 using X-ray images

Al-Bawi, A., Al-Kaabi, K., Jeryo, M., & Al-Fatlawi, A. (2020) · Research on Biomedical Engineering · doi:10.1007/s42600-020-00110-7 · Cited by 18

Improving effectiveness of different deep learning-based models for detecting COVID-19 from computed tomography (CT) imagesPreprint

Acar, E., Şahin, E., & Yılmaz, İ. (2020) · medRxiv · doi:10.1101/2020.06.12.20129643 · Cited by 17

Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks

Sehanobish, A., Ravindra, N. G., & van Dijk, D. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i6.16619 · Cited by 17

A Weakly Supervised Region-Based Active Learning Method for COVID-19 Segmentation in CT ImagesPreprint

Laradji, I., Rodríguez, P., Branchaud-Charron, F., Lensink, K., Atighehchian, P., Parker, W., Vázquez, D., & Nowrouzezahrai, D. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.07012 · Cited by 17

Construction and validation of a machine learning‐based nomogram: A tool to predict the risk of getting severe coronavirus disease 2019 (COVID‐19)

Yao, Z., Zheng, X., Zheng, Z., Wu, K., & Zheng, J. (2021) · Immunity Inflammation and Disease · doi:10.1002/iid3.421 · Cited by 17

Segmentation and Evaluation of COVID-19 Lesion from CT scan Slices - A Study with Kapur/Otsu Function and Cuckoo Search AlgorithmPreprint

Satapathy, S. C., Hemanth, D. J., Kadry, S., Manogaran, G., Hannoon, N. M. S., & Rajinikanth, V. (2020) · doi:10.21203/rs.3.rs-40148/v1 · Cited by 17

Curbing the AI-induced enthusiasm in diagnosing COVID-19 on chest X-Rays: the present and the near-futurePreprint

Burlacu, A., Crișan-Dabija, R. A., Popa, I. V., Artene, B., Birzu, V., Pricop, M., Pleșoianu, C., & Generali, D. (2020) · medRxiv · doi:10.1101/2020.04.28.20082776 · Cited by 16

Short-term forecasts of COVID-19 spread across Indian states until 1 May 2020Preprint

Poonia, N., & Azad, S. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.13538 · Cited by 16

AIDCOV: An Interpretable Artificial Intelligence Model for Detection of COVID-19 from Chest Radiography ImagesPreprint

Zokaeinikoo, M., Kazemian, P., Mitra, P., et al. (2020) · medRxiv · doi:10.1101/2020.05.24.20111922 · Cited by 16

A Novel Smart City Based Framework on Perspectives for application of Machine Learning in combatting COVID-19Preprint

Ezugwu, A. E.-S., Hashem, M., Oyelade, O. N., et al. (2020) · medRxiv · doi:10.1101/2020.05.18.20105577 · Cited by 16

Rapid Development of Competitive Translation Engines for Access to Multilingual COVID-19 Information

Way, A., Haque, R., Xie, G., Gaspari, F., Popović, M., & Poncelas, A. (2020) · Informatics · doi:10.3390/informatics7020019 · Cited by 16

Automatic Detection of COVID-19 Cases on X-ray images Using Convolutional Neural NetworksPreprint

Soares, L. P., & Soares, C. P. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.05494 · Cited by 16

Development of a severity of disease score and classification model by machine learning for hospitalized COVID-19 patientsPreprint

Marcos, M., Belhassen‐García, M., Sánchez-Puente, A., et al. (2020) · medRxiv · doi:10.1101/2020.07.13.20150177 · Cited by 16

Virtual Screening on Indonesian Herbal Compounds as COVID-19 Supportive Therapy: Machine Learning and Pharmacophore Modeling ApproachesPreprint

Erlina, L., Paramita, R. I., Kusuma, W. A., Fadilah, F., Tedjo, A., Pratomo, I. P., Ramadhanti, N. S., Nasution, A. K., Surado, F. K., Fitriawan, A., et al. (2020) · doi:10.21203/rs.3.rs-29119/v1 · Cited by 16

Multimodal Behavior Analysis in the Wild

Alameda-Pineda, X., Ricci, E., & Sebe, N. (2018) · Elsevier eBooks · doi:10.1016/c2017-0-01387-3 · Cited by 16

Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach (Preprint)Preprint

Xue, J., Chen, J., Hu, R., et al. (2020) · doi:10.2196/preprints.20550 · Cited by 16

Fast and accurate detection of Covid-19-related pneumonia from chest X-ray images with novel deep learning modelPreprint

Mm, R., Faza, A., Lubis, L. E., Yunus, R. E., Salamah, T., Handayani, D. P., Lestariningsih, I., Resa, A., Alam, C., Prajitno, P., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.04562 · Cited by 16

Improvement of Quantum Evolutionary Algorithm with a Functional Sized Population

Tayarani, M., & Reza, A. T. M. (2009) · Advances in intelligent and soft computing · doi:10.1007/978-3-540-89619-7_38 · Cited by 15

What an “Ehm” Leaks About You: Mapping Fillers into Personality Traits with Quantum Evolutionary Feature Selection Algorithms

Tayarani, M., Esposito, A. A., & Vinciarelli, A. (2019) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2019.2930695 · Cited by 15

Development and Validation of a Diagnostic Nomogram to Predict COVID-19 PneumoniaPreprint

Wang, Z., Weng, J., Li, Z., Hou, R., Zhou, L., Ye, H., Chen, Y., Yang, T., Chen, D., Wang, L., et al. (2020) · medRxiv · doi:10.21203/rs.3.rs-22140/v1 · Cited by 15

Predicting community mortality risk due to CoVID-19 using machine learning and development of a prediction toolPreprint

Das, A., Mishra, S. R., & Gopalan, S. S. (2020) · medRxiv · doi:10.1101/2020.04.27.20081794 · Cited by 15

Early risk assessment for COVID-19 patients from emergency department data using machine learningPreprint

Heldt, F. S., Vizcaychipi, M. P., Peacock, S., et al. (2020) · medRxiv · doi:10.1101/2020.05.19.20086488 · Cited by 15

Artificial Intelligence and Drones to Combat COVID - 19Preprint

Preethika, T., Vaishnavi, P., Agnishwar, J., Padmanathan, K., Umashankar, S., Annapoorani, S., Subash, M., & Aruloli, K. (2020) · Preprints.org · doi:10.20944/preprints202006.0027.v1 · Cited by 15

COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literaturePreprint

Peng, Y., Tang, Y., Lee, S., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.06177 · Cited by 15

A Recurrent Neural Network and Differential Equation Based Spatiotemporal Infectious Disease Model with Application to COVID-19Preprint

Li, Z., Zheng, Y., Xin, J. X., & Zhou, G. (2020) · medRxiv · doi:10.1101/2020.07.20.20158568 · Cited by 15

Fast Deep Learning Computer-Aided Diagnosis against the Novel COVID-19 pandemic from Digital Chest X-ray ImagesPreprint

Al–antari, M. A., Hua, C.-H., & Lee, S. (2020) · doi:10.21203/rs.3.rs-36353/v1 · Cited by 15

COVID-19 Machine Learning Based Survival Analysis and Discharge Time Likelihood Prediction Using Clinical DataPreprint

Nemati, M., Ansary, J., & Nemati, N. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3584518 · Cited by 15

Genetic algorithm with cross-validation-based epidemic model and application to the early diffusion of COVID-19 in Algeria

Rouabah, M. T., Tounsi, A., & Belaloui, N. E. (2021) · Scientific African · doi:10.1016/j.sciaf.2021.e01050 · Cited by 15

Estimating underdiagnosis of COVID-19 with nowcasting and machine learning

Garcia, L. P., Gonçalves, A. V., de Andrade, M. P., Pedebôs, L. A., Vidor, A. C., Zaina, R., Hallal, A. L. C., Canto, G. D. L., Traebert, J. L., de Araújo, G. M., et al. (2021) · Revista Brasileira de Epidemiologia · doi:10.1590/1980-549720210047 · Cited by 15

Secret Key Rate Adaption for Multicarrier Continuous-Variable Quantum Key Distribution

Gyöngyösi, L., & Imre, S. (2019) · SN Computer Science · doi:10.1007/s42979-019-0027-7 · Cited by 14

Identifying novel factors associated with COVID-19 transmission and fatality using the machine learning approachPreprint

Li, M., Zhang, Z., Cao, W., et al. (2020) · medRxiv · doi:10.1101/2020.06.10.20127472 · Cited by 14

A mathematical epidemic model using genetic fitting algorithm with cross-validation and application to early dynamics of COVID-19 in AlgeriaPreprint

Rouabah, M. T., Tounsi, A., & Belaloui, N. E. (2020) · arXiv (Cornell University) · Cited by 14

Continual BERT: Continual Learning for Adaptive Extractive Summarization of COVID-19 LiteraturePreprint

Park, J. W. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.03405 · Cited by 14

Using Deep Convolutional Neural Networks to Diagnose COVID-19 From Chest X-Ray ImagesPreprint

Zhong, Y. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.09695 · Cited by 14

A Markov Model for Prediction of Corona Virus COVID-19 in India- A Statistical Study

(2020) · Journal of Xidian University · doi:10.37896/jxu14.4/164 · Cited by 14

A Comprehensive Study on Classification of COVID-19 on Computed Tomography with Pretrained Convolutional Neural NetworksPreprint

Pham, T. D. (2020) · doi:10.36227/techrxiv.12340421.v1 · Cited by 14

Improvement of the performance of the Quantum-inspired Evolutionary Algorithms: structures, population, operators

Tayarani-N, M. H., & Akbarzadeh-T, M.-R. (2014) · Evolutionary Intelligence · doi:10.1007/s12065-014-0120-8 · Cited by 13

A Viral Warning for Change. COVID-19 Versus the Red Cross: Better Solutions Via Blockchain and Artificial IntelligencePreprint

Johnstone, S. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3530756 · Cited by 13

TRACKING AND PREDICTING COVID-19 RADIOLOGICAL TRAJECTORY USING DEEP LEARNING ON CHEST X-RAYS: INITIAL ACCURACY TESTINGPreprint

Duchesne, S., Gourdeau, D., Archambault, P. M., et al. (2020) · medRxiv · doi:10.1101/2020.05.01.20086207 · Cited by 13

How well can we forecast the COVID-19 pandemic with curve fitting and recurrent neural networks?Preprint

Zhao, Z., Nehil-Puleo, K., & Zhao, Y. (2020) · medRxiv · doi:10.1101/2020.05.14.20102541 · Cited by 13

Optimisation of Non-Pharmaceutical Measures in COVID-19 Growth via Neural Networks

Riccardi, A., Gemignani, J., Fernández‐Navarro, F., & Heffernan, A. (2021) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2020.3046012 · Cited by 13

Machine Learning Maps Research Needs in COVID-19 LiteraturePreprint

Doanvo, A., Qian, X., Ramjee, D., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.06.11.145425 · Cited by 13

An interpretable mortality prediction model for COVID-19 patients – alternative approachPreprint

Gemmar, P. (2020) · medRxiv · doi:10.1101/2020.06.14.20130732 · Cited by 13

End-to-End AI-Based Point-of-Care Diagnosis System for Classifying Respiratory Illnesses and Early Detection of COVID-19Preprint

Belkacem, A. N., Ouhbi, S., Lakas, A., Benkhelifa, E., & Chen, C. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.15469 · Cited by 13

A novel and reliable deep learning web-based tool to detect COVID-19 infection form chest CT-scanPreprint

Saeedi, A., Saeedi, M., & Maghsoudi, A. (2020) · arXiv (Cornell University) · Cited by 13

Agent-based Simulation Model and Deep Learning Techniques to Evaluate and Predict Transportation Trends around COVID-19Preprint

Wang, D., Zuo, F., Gao, J., He, B. Y., Bian, Z., Bernardes, S. D., Na, C., Wang, J., Petinos, J., Özbay, K. M. A., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.09648 · Cited by 13

$\alpha$-Satellite: An AI-driven System and Benchmark Datasets for Hierarchical Community-level Risk Assessment to Help Combat COVID-19Preprint

Ye, Y., Hou, S., Fan, Y., Qian, Y., Zhang, Y., Sun, S., Peng, Q., & Laparo, K. (2020) · arXiv (Cornell University) · Cited by 13

Transfer learning based ensemble support vector machine model for automated COVID-19 detection using lung computerized tomography scan dataPreprint

Singh, M. P., Bansal, S., Ahuja, S., et al. (2020) · Research Square · doi:10.21203/rs.3.rs-32493/v1 · Cited by 12

ProgNet: Covid-19 prognosis using recurrent and convolutional neural networksPreprint

Fakhfakh, M. A., Bouaziz, B., Gargouri, F., et al. (2020) · medRxiv · doi:10.1101/2020.05.06.20092874 · Cited by 12

Hypergraph Learning for Identification of COVID-19 with CT ImagingPreprint

Di, D., Shi, F., Yan, F., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.04043 · Cited by 12

ESTIMATING UNDERDIAGNOSIS OF COVID-19 WITH NOWCASTING AND MACHINE LEARNING – EXPERIENCE FROM BRAZILPreprint

Garcia, L. P., Gonçalves, A. V., de Andrade, M. P., et al. (2020) · medRxiv · doi:10.1101/2020.07.01.20144402 · Cited by 12

Parameters Estimation of Generalized Richards Model for COVID-19 Cases in Indonesia Using Genetic Algorithm

Rayungsari, M., Aufin, M., & Imamah, N. (2020) · Jambura Journal of Biomathematics (JJBM) · doi:10.34312/jjbm.v1i1.6910 · Cited by 12

Covid-19 Pandemic: Application of Machine Learning Time Series Analysis for Prediction of Human FuturePreprint

Chaurasia, V., & Pal, S. (2020) · doi:10.21203/rs.3.rs-39149/v1 · Cited by 12

Efficient Deep Learning Model for COVID-19 Detection in large CT images datasets: A cross-dataset analysisPreprint

Silva, P., Luz, E. J. D. S., Silva, G., et al. (2020) · Research Square · doi:10.21203/rs.3.rs-41062/v1 · Cited by 12

Social-Group-Optimization Assisted Kapur’s Entropy and Morphological Segmentation for Automated Detection of COVID-19 Infection from Computed Tomography ImagesPreprint

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