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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

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Showing 51-75 of 84 citing articles:

Attributed Network Embedding Model for Exposing COVID-19 Spread Trajectory Archetypes
Junwei Ma, Bo Li, Qingchun Li, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 2
A Boosted Evolutionary Neural Architecture Search for Timeseries Forecasting with Application to South African COVID-19 Cases
Solomon Oluwole Akinola, Qing‐Guo Wang, Peter Olukanmi, et al.
International Journal of Online and Biomedical Engineering (iJOE) (2023) Vol. 19, Iss. 14, pp. 107-130
Open Access | Times Cited: 2
An Effective Video Surveillance System by using CNN for COVID-19
Basetty Mallikarjuna, D. Anusha, Sethu Ram M., et al.
Advances in wireless technologies and telecommunication book series (2021), pp. 88-102
Closed Access | Times Cited: 5
Attributed network embedding model for exposing COVID-19 spread trajectory archetypes
Junwei Ma, Bo Li, Qingchun Li, et al.
International Journal of Data Science and Analytics (2024)
Closed Access
Interpretable Machine Learning for COVID-19: An Empirical Study on Severity Prediction Task
Han Wu, Wenjie Ruan, Jiangtao Wang, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 4
Inter-Series Attention Model for COVID-19 Forecasting
Xiaoyong Jin, Yu-Xiang Wang, Xifeng Yan
arXiv (Cornell University) (2020)
Open Access | Times Cited: 4
Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting
Lijing Wang, Aniruddha Adiga, Srinivasan Venkatramanan, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 4
Estimation of Daily Cases, Deaths, Serious Patients and Recovering Patients of Covid-19 in Turkey with Machine Learning Methods
Figen Özen
Journal of Advanced Research in Natural and Applied Sciences (2022) Vol. 8, Iss. 4, pp. 662-676
Open Access | Times Cited: 3
DARCVAA: A Deep Neural Networks Based Framework for Detecting Adverse Reactions of COVID-19 Vaccines and Association Analysis
Ngamwal Sinruwng, Yogita Thakran, Vipin Pal, et al.
SN Computer Science (2024) Vol. 5, Iss. 5
Closed Access
Applications of artificial intelligence with cloud computing in promoting social distancing to combat COVID-19
Mohammed G. Al-Hamiri, Hayder Fadhil Abdulsada, Laith A. Abdul-Rahaim
Indonesian Journal of Electrical Engineering and Computer Science (2021) Vol. 24, Iss. 3, pp. 1550-1550
Open Access | Times Cited: 4
Early Indicators of COVID-19 Spread Risk Using Digital Trace Data of Population Activities
Gao X, Fan Chun, Y. Tony Yang, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 3
A Comparative Evaluation of Probabilistic and Deep Learning Approaches for Vehicular Trajectory Prediction
Luis Irio, Rodolfo Oliveira
IEEE Open Journal of Vehicular Technology (2021) Vol. 2, pp. 140-150
Open Access | Times Cited: 3
Survey of Applications of Neural Networks and Machine Learning to COVID-19 Predictions
Richard S. Segall
Advances in computational intelligence and robotics book series (2021), pp. 30-57
Closed Access | Times Cited: 3
Data-driven contact network models of COVID-19 reveal trade-offs between costs and infections for optimal local containment policies
Chao Fan, Xiangqi Jiang, Ronald Lee, et al.
Cities (2022) Vol. 128, pp. 103805-103805
Open Access | Times Cited: 2
Survey of Recent Applications of Artificial Intelligence for Detection and Analysis of COVID-19 and Other Infectious Diseases
Richard S. Segall, Vidhya Sankarasubbu
International Journal of Artificial Intelligence and Machine Learning (2022) Vol. 12, Iss. 2, pp. 1-30
Open Access | Times Cited: 2
Application of Ensemble Techniques Based Sentiment Analysis to Assess the Adoption Rate of E-Learning During Covid-19 Among the Spectrum of Learners
S. Sirajudeen, Balaganesh, Haleema, et al.
Communications in computer and information science (2021), pp. 187-202
Closed Access | Times Cited: 2
An Adaptable LSTM Network Predicting COVID-19 Occurrence Using Time Series Data
Anthony Li, Nikhil Yadav
(2021)
Closed Access | Times Cited: 2
Forecasting High-risk Areas of COVID-19 Infection Through Socioeconomic and Static Spatial Analysis
Abdulaziz Alhamadani, Shailik Sarkar, Lei Zhang, et al.
2021 IEEE International Conference on Big Data (Big Data) (2021), pp. 4313-4322
Closed Access | Times Cited: 2
Predict the Risk Level in Iraqi Governorates According to the Spread of COVID-19 Using Data Mining
Ibtisam Abbas Othman, Ban Sharief Mustafa
NTU Journal of Pure Sciences (2022) Vol. 1, Iss. 2, pp. 22-28
Open Access | Times Cited: 1
AI Techniques for Forecasting Epidemic Dynamics: Theory and Practice
Aniruddha Adiga, Bryan Lewis, Simon A. Levin, et al.
Springer eBooks (2022), pp. 193-228
Closed Access | Times Cited: 1
Forecasting Lassa Fever Outbreak Progression with Machine Learning
Akinola Solomon Oluwole, Thembinkosi Nkonyana
2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) (2022), pp. 1-5
Closed Access | Times Cited: 1
Memory-Dependent Forecasting of COVID-19: The Flexibility of Extrapolated Kernel Least Mean Square Algorithm
Noor Atinah Ahmad, Mohd Hafiz Mohd
(2021)
Closed Access | Times Cited: 1
Global and local interpretation of black-box machine learning models to determine prognostic factors from early COVID-19 data
Ananya Jana, Carlos D. Minacapelli, Vinod K. Rustgi, et al.
(2021), pp. 7-7
Open Access | Times Cited: 1
Memory-Dependent Forecasting of COVID-19: The Flexibility of Extrapolated Kernel Least Mean Square Algorithm
Noor Atinah Ahmad, Mohd Hafiz Mohd
(2021)
Closed Access | Times Cited: 1
Evaluating the Effectiveness of Digital Social Mobility Data in COVID-19 Predictive Models: A Scoping Review (Preprint)
Kristopher Dylan Espiritu, Pedro Elkind Velmovitsky, Rajan Grewal, et al.
(2023)
Closed Access

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