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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:

Towards Providing Effective Data-Driven Responses to Predict the Covid-19 in São Paulo and Brazil
Fabio Amaral, Wallace Casaca, Cassio M. Oishi, et al.
Sensors (2021) Vol. 21, Iss. 2, pp. 540-540
Open Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

Temporal deep learning architecture for prediction of COVID-19 cases in India
Hanuman Verma, Saurav Mandal, Akshansh Gupta
Expert Systems with Applications (2022) Vol. 195, pp. 116611-116611
Open Access | Times Cited: 54
Interpretable Temporal Attention Network for COVID-19 forecasting
Binggui Zhou, Guanghua Yang, Zheng Shi, et al.
Applied Soft Computing (2022) Vol. 120, pp. 108691-108691
Open Access | Times Cited: 31
Integrating artificial intelligence with mechanistic epidemiological modeling: a scoping review of opportunities and challenges
Yang Ye, Abhishek Pandey, Carolyn E. Bawden, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access
Data-Driven Analytics Leveraging Artificial Intelligence in the Era of COVID-19: An Insightful Review of Recent Developments
Abdul Majeed, Seong Oun Hwang
Symmetry (2021) Vol. 14, Iss. 1, pp. 16-16
Open Access | Times Cited: 36
Multi-generational SIR modeling: Determination of parameters, epidemiological forecasting and age-dependent vaccination policies
Eduardo Lima Campos, Rubens Penha Cysne, Alexandre L. Madureira, et al.
Infectious Disease Modelling (2021) Vol. 6, pp. 751-765
Open Access | Times Cited: 29
Disjoint and Functional Principal Component Analysis for Infected Cases and Deaths Due to COVID-19 in South American Countries with Sensor-Related Data
Carlos Martin‐Barreiro, John A. Ramirez-Figueroa, Xavier Cabezas, et al.
Sensors (2021) Vol. 21, Iss. 12, pp. 4094-4094
Open Access | Times Cited: 28
Risk Factors Associated with Mortality in Hospitalized Patients with COVID-19 during the Omicron Wave in Brazil
Marilaine Colnago, Giovana A. Benvenuto, Wallace Casaca, et al.
Bioengineering (2022) Vol. 9, Iss. 10, pp. 584-584
Open Access | Times Cited: 21
Modeling Provincial Covid-19 Epidemic Data Using an Adjusted Time-Dependent SIRD Model
Luisa Ferrari, G Gerardi, Giancarlo Manzi, et al.
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 12, pp. 6563-6563
Open Access | Times Cited: 26
Dual attention-based sequential auto-encoder for Covid-19 outbreak forecasting: A case study in Vietnam
Phu Pham, Witold Pedrycz, Bay Vo
Expert Systems with Applications (2022) Vol. 203, pp. 117514-117514
Open Access | Times Cited: 15
Forecasting COVID-19 spreading through an ensemble of classical and machine learning models: Spain’s case study
Ignacio Heredia, Judith Sáinz-Pardo Díaz, María Castrillo, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 8
High SARS-CoV-2 infection rate after resuming professional football in São Paulo, Brazil
Bruno Gualano, Gisele Mendes Brito, Ana Jéssica Pinto, et al.
British Journal of Sports Medicine (2021) Vol. 56, Iss. 18, pp. 1004-1007
Open Access | Times Cited: 19
Simulating Immunization Campaigns and Vaccine Protection Against COVID-19 Pandemic in Brazil
Fabio Amaral, Wallace Casaca, Cassio M. Oishi, et al.
IEEE Access (2021) Vol. 9, pp. 126011-126022
Open Access | Times Cited: 17
Forecasting a New Type of Virus Spread: A Case Study of COVID-19 with Stochastic Parameters
Victor Zakharov, Yu. Е. Balykina, Igor Ilin, et al.
Mathematics (2022) Vol. 10, Iss. 20, pp. 3725-3725
Open Access | Times Cited: 10
A data-driven epidemic model with human mobility and vaccination protection for COVID-19 prediction
Ruqi Li, Yurong Song, Hongbo Qu, et al.
Journal of Biomedical Informatics (2023) Vol. 149, pp. 104571-104571
Closed Access | Times Cited: 5
Forecasting the Long-Term Trends of Coronavirus Disease 2019 (COVID-19) Epidemic Using the Susceptible-Infectious-Recovered (SIR) Model
Agus Priyono Kartono, Savira Vita Karimah, Setyanto Tri Wahyudi, et al.
Infectious Disease Reports (2021) Vol. 13, Iss. 3, pp. 668-684
Open Access | Times Cited: 6
Using machine learning models to predict the duration of the recovery of COVID-19 patients hospitalized in Fangcang shelter hospital during the Omicron BA. 2.2 pandemic
Yü Xu, Ye Wei, Qiuyue Song, et al.
Frontiers in Medicine (2022) Vol. 9
Open Access | Times Cited: 4
Interpreting County-Level COVID-19 Infections using Transformer and Deep Learning Time Series Models
Md. Khairul Islam, Yingzheng Liu, Andrej Erkelens, et al.
(2023), pp. 266-277
Closed Access | Times Cited: 2
A Novel Approach on Deep Learning—Based Decision Support System Applying Multiple Output LSTM-Autoencoder: Focusing on Identifying Variations by PHSMs’ Effect over COVID-19 Pandemic
Yong‐Ju Jang, Min-Seung Kim, Chan-Ho Lee, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 11, pp. 6763-6763
Open Access | Times Cited: 3
Aplicação de Redes de Deep Learning Recurrent Neural Network, Long Short-Term Memory e Gated Recurrent Unit na Predição da COVID-19 no Cenário Pós-Vacinação
Rafaella Silva Ferreira, Wallace Casaca, Marilaine Colnago
(2024), pp. 145-156
Closed Access
Diagnosing COVID-19 on Limited Data: A Comparative Study of Machine Learning Methods
Rita Zgheib, Firuz Kamalov, Ghazar Chahbandarian, et al.
Lecture notes in computer science (2021), pp. 616-627
Closed Access | Times Cited: 4
Local protection bubbles: an interpretation of the slowdown in the spread of coronavirus in the city of São Paulo, Brazil, in July 2020
José Paulo Guedes Pinto, P. Camargo Magalhaes, Gerusa Maria Figueiredo, et al.
Cadernos de Saúde Pública (2023) Vol. 39, Iss. 11
Open Access | Times Cited: 1
Tracking machine learning models for pandemic scenarios: a systematic review of machine learning models that predict local and global evolution of pandemics
Marcelo Benedeti Palermo, Lucas Micol Policarpo, Cristiano André da Costa, et al.
Network Modeling Analysis in Health Informatics and Bioinformatics (2022) Vol. 11, Iss. 1
Open Access | Times Cited: 2
Space-Distributed Traffic-Enhanced LSTM-Based Machine Learning Model for COVID-19 Incidence Forecasting
Mario Muñoz-Organero
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-12
Open Access | Times Cited: 2
Neural Networks Architecture for COVID-19 Early Detection
Rita Zgheib, Ghazar Chahbandarian, Firuz Kamalov, et al.
2022 International Symposium on Networks, Computers and Communications (ISNCC) (2021), pp. 1-6
Closed Access | Times Cited: 1
Dynamic transmission modeling of COVID-19 to support decision-making in Brazil: A scoping review in the pre-vaccine era
Gabriel Berg de Almeida, Lorena Mendes Simon, Ângela Maria Bagattini, et al.
PLOS Global Public Health (2023) Vol. 3, Iss. 12, pp. e0002679-e0002679
Open Access
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