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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.

Requested Article:

COVINet: A deep learning-based and interpretable prediction model for the county-wise trajectories of COVID-19 in the United States
Yukang Jiang, Ting Tian, Wenting Zhou, et al.
medRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 11

Showing 11 citing articles:

Applications of artificial intelligence in battling against covid-19: A literature review
Mohammad-H. Tayarani N.
Chaos Solitons & Fractals (2020) Vol. 142, pp. 110338-110338
Open Access | Times Cited: 195
On the reliability of predictions on Covid-19 dynamics: A systematic and critical review of modelling techniques
Janyce Gnanvi, Kolawolé Valère Salako, Gaëtan Brezesky Kotanmi, et al.
Infectious Disease Modelling (2021) Vol. 6, pp. 258-272
Open Access | Times Cited: 94
Hybrid deep learning of social media big data for predicting the evolution of COVID-19 transmission
Alvin Wei Ze Chew, Yue Pan, Ying Wang, et al.
Knowledge-Based Systems (2021) Vol. 233, pp. 107417-107417
Open Access | Times Cited: 34
On the reliability of predictions on Covid-19 dynamics: a systematic and critical review of modelling techniques
Janyce Gnanvi, Kolawolé Valère Salako, Brezesky Kotanmi, et al.
medRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 24
Disease Spread Control in Cruise Ships: Monitoring, Simulation, and Decision Making
Georgios Triantafyllou, Panagiotis G. Kalozoumis, Eirini Cholopoulou, et al.
Springer eBooks (2024), pp. 93-141
Closed Access | Times Cited: 1
A coarse‐refine segmentation network for COVID‐19 CT images
Ziwang Huang, Liang Li, Xiang Zhang, et al.
IET Image Processing (2021) Vol. 16, Iss. 2, pp. 333-343
Open Access | Times Cited: 8
Biology-Informed Recurrent Neural Network for Pandemic Prediction Using Multimodal Data
Zhiwei Ding, Feng Sha, Yi Zhang, et al.
Biomimetics (2023) Vol. 8, Iss. 2, pp. 158-158
Open Access | Times Cited: 2
Inter-Series Attention Model for COVID-19 Forecasting
Xiaoyong Jin, Yu-Xiang Wang, Xifeng Yan
arXiv (Cornell University) (2020)
Open Access | Times Cited: 4
DeepCOVIDNet: An Interpretable Deep Learning Model for Predictive Surveillance of COVID-19 Using Heterogeneous Features and their Interactions
Ankit Ramchandani, Chao Fan, Ali Mostafavi
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 3
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
Forecasting COVID-19 Hotspots in Florida Public Schools: A Machine Learning Approach
Mingming Peng, Askal Ayalew Ali, Hongmei Chi
2021 IEEE International Conference on Big Data (Big Data) (2023), pp. 3721-3730
Closed Access
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