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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:

An interpretable hybrid predictive model of COVID-19 cases using autoregressive model and LSTM
Yangyi Zhang, Sui Tang, Yu Guo
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 14

Showing 14 citing articles:

La radiología como pilar de la investigación COVID-19 basada en IA: perspectivas de un análisis bibliométrico diverso
Antonio Navarro Ballester, Jose Bonilla, L.H. Ros Mendoza, et al.
Radiología (2025)
Closed Access
Supervised Learning Models, Statistical Models or Hybrid Models? A Prediction of Clean Energy Stock Based on Fear and Fundamental Factors
Y. H. Zheng, Brian M. Lucey
(2025), pp. 100006-100006
Open Access
Zero-Shot Traffic Flow Prediction with Large Language Models: A Comparison with Deep Learning Approaches
Yue Li, Qunshan Zhao, Mingshu Wang
Research Square (Research Square) (2025)
Closed Access
Progression of COVID-19 Cases in Telangana State by using ARIMA, MLP, ELM and LSTM Prediction Models by Retrospective Confirmation
M. Rajendar, Mallikarjuna Reddy Doodipala, Mr Nagesh, et al.
Indian Journal of Science and Technology (2024) Vol. 17, Iss. 12, pp. 1159-1166
Open Access | Times Cited: 2
Towards Improved XAI-Based Epidemiological Research into the Next Potential Pandemic
Hamed Khalili, Maria A. Wimmer
Life (2024) Vol. 14, Iss. 7, pp. 783-783
Open Access | Times Cited: 2
Enhancing infectious disease prediction model selection with multi-objective optimization: an empirical study
Deren Xu, Weng Howe Chan, Habibollah Haron
PeerJ Computer Science (2024) Vol. 10, pp. e2217-e2217
Open Access | Times Cited: 1
TS2ARCformer: A Multi-Dimensional Time Series Forecasting Framework for Short-Term Load Prediction
Songjiang Li, Wenxin Zhang, Peng Wang
Energies (2023) Vol. 16, Iss. 15, pp. 5825-5825
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
Forecasting daily COVID-19 cases with gradient boosted regression trees and other methods: evidence from U.S. cities
Anindya Sen, Nathaniel T. Stevens, Nam Tran, et al.
Frontiers in Public Health (2023) Vol. 11
Open Access | Times Cited: 2
An Accurate Model for Covid-19 Positive Cases in India by using Traditional ARIMA and Artificial Neural Networks (LSTM and Bi-LSTM)
M. Rajendar, D. Mallikarjuna Reddy, V. Nagaraju
Indian Journal of Science and Technology (2024) Vol. 17, Iss. 23, pp. 2421-2429
Open Access
Epidemiological modeling of monkeypox clades: a dual-strain SEIR approach with stability, bifurcation, and sensitivity analysis
Dounia Bentaleb, Zakaria Khatar, Saïda Amine
Modeling Earth Systems and Environment (2024)
Closed Access
Embracing the power of ensemble forecasting: A novel hybrid approach for advanced predictive modeling
Isha Malhotra, Nidhi Goel
Information Processing & Management (2024) Vol. 62, Iss. 1, pp. 103954-103954
Closed Access
Global Infectious Disease Early Warning Models: An Updated Review and Lessons from the COVID-19 Pandemic
Weihua Hu, Huimin Sun, Yongyue Wei, et al.
Infectious Disease Modelling (2024) Vol. 10, Iss. 2, pp. 410-422
Open Access
Impact of COVID-19 Interventions on Respiratory and Intestinal Infectious Disease Notifications — Jiangsu Province, China, 2020–2023
Ziying Chen, Xin Liu, Jinxing Guan, et al.
Deleted Journal (2024) Vol. 6, Iss. 41, pp. 1059-1064
Closed Access
Forecasting Time Series Covid 19 Using Deep Learning Methods: South America Comparative Case Study
Miguel Alfaro, Manuel Vargas, Guillermo Fuertes, et al.
Research Square (Research Square) (2023)
Open Access
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