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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:

Deep Spatiotemporal Model for COVID-19 Forecasting
Mario Muñoz-Organero, Paula Queipo-Álvarez
Sensors (2022) Vol. 22, Iss. 9, pp. 3519-3519
Open Access | Times Cited: 10

Showing 10 citing articles:

Supervised machine learning: A new method to predict the outcomes following exercise intervention in children with autism spectrum disorder
Zhiyuan Sun, Yunhao Yuan, Xiaoxiao Dong, et al.
International Journal of Clinical and Health Psychology (2023) Vol. 23, Iss. 4, pp. 100409-100409
Open Access | Times Cited: 9
A new RNN based machine learning model to forecast COVID-19 incidence, enhanced by the use of mobility data from the bike-sharing service in Madrid
Mario Muñoz-Organero, Patricia Callejo, Miguel Ángel Hombrados-Herrera
Heliyon (2023) Vol. 9, Iss. 6, pp. e17625-e17625
Open Access | Times Cited: 6
A Deep Graph Neural Network Approach for Assessing Origin Destination Traffic Flow Estimates Based on COVID-19 Data
Mario Muñoz-Organero, Víctor Corcoba Magaña
IEEE Access (2024) Vol. 12, pp. 119003-119014
Open Access | Times Cited: 1
Projecting COVID-19 intensive care admissions for policy advice, the Netherlands, February 2020 to January 2021
Don Klinkenberg, Jantien A. Backer, Nicolette F. de Keizer, et al.
Eurosurveillance (2024) Vol. 29, Iss. 10
Open Access
Enhancing COVID-19 Prediction: Optimized Random Forest Classifier with Feature Selection
N. Komal Kumar, G. Rajkumar, N. Poojitha, et al.
(2024), pp. 1-6
Closed Access
Projecting COVID-19 intensive care admissions in the Netherlands for policy advice: February 2020 to January 2021
Don Klinkenberg, Jantien A. Backer, Nicolette F. de Keizer, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 1
Using Traffic Sensors in Smart Cities to Enhance a Spatio-Temporal Deep Learning Model for COVID-19 Forecasting
Mario Muñoz-Organero
Mathematics (2023) Vol. 11, Iss. 18, pp. 3904-3904
Open Access
A data-driven framework to assess population dynamics during novel coronavirus outbreaks: A case study on Xiamen Island, China
Peng Wang, Jinliang Huang
PLoS ONE (2023) Vol. 18, Iss. 11, pp. e0293803-e0293803
Open Access
Utilizing time series for forecasting the development trend of coronavirus: A validation process
Xusong Zhang, Feng Wang
Journal of Computational Methods in Sciences and Engineering (2023) Vol. 23, Iss. 6, pp. 2923-2935
Closed Access
COVID-19 incidence estimates and forecast by metaprediction for the Comunidad de Madrid *
A. Martinez, Mario Muñoz-Organero, David Moriña, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2023), pp. 3362-3369
Closed Access
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