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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:

Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting
Lijing Wang, Aniruddha Adiga, Srinivasan Venkatramanan, et al.
2021 IEEE International Conference on Big Data (Big Data) (2020), pp. 3846-3855
Open Access | Times Cited: 20

Showing 20 citing articles:

Application of machine learning in the prediction of COVID-19 daily new cases: A scoping review
Soudeh Ghafouri‐Fard, Hossein Mohammad‐Rahimi, Parisa Motie, et al.
Heliyon (2021) Vol. 7, Iss. 10, pp. e08143-e08143
Open Access | Times Cited: 59
Explicit Context Integrated Recurrent Neural Network for applications in smart environments
Rashmi Dutta Baruah, Mario Muñoz-Organero
Expert Systems with Applications (2024) Vol. 255, pp. 124752-124752
Closed Access | Times Cited: 6
iPREDICT: AI enabled proactive pandemic prediction using biosensing wearable devices
Muhammad Sajid Riaz, Maria Shaukat, Tabish Saeed, et al.
Informatics in Medicine Unlocked (2024) Vol. 46, pp. 101478-101478
Open Access | Times Cited: 4
Machine learning for data-centric epidemic forecasting
Alexander Rodríguez, Harshavardhan Kamarthi, Pulak Agarwal, et al.
Nature Machine Intelligence (2024)
Closed Access | Times Cited: 3
Role of miR-424 in the carcinogenesis
Soudeh Ghafouri‐Fard, Arian Askari, Bashdar Mahmud Hussen, et al.
Clinical & Translational Oncology (2023) Vol. 26, Iss. 1, pp. 16-38
Open Access | Times Cited: 9
All Models Are Useful: Bayesian Ensembling for Robust High Resolution COVID-19 Forecasting
Aniruddha Adiga, Lijing Wang, Benjamin Hurt, et al.
(2021), pp. 2505-2513
Open Access | Times Cited: 22
The emerging role of miR-20b in human cancer and other disorders: Pathophysiology and therapeutic implications
Sheyda Khalilian, Hamid Abedinlou, Bashdar Mahmud Hussen, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 12
All Models Are Useful: Bayesian Ensembling for Robust High Resolution COVID-19 Forecasting
Aniruddha Adiga, Lijing Wang, Benjamin Hurt, et al.
medRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 15
Epidemic Dynamics via Wavelet Theory and Machine Learning with Applications to Covid-19
Tô Tat Dat, Protin Frédéric, Hang Nguyen Thi Thu, et al.
Biology (2020) Vol. 9, Iss. 12, pp. 477-477
Open Access | Times Cited: 14
Phase-Informed Bayesian Ensemble Models Improve Performance of COVID-19 Forecasts
Aniruddha Adiga, Gursharn Kaur, Lijing Wang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2023) Vol. 37, Iss. 13, pp. 15647-15653
Open Access | Times Cited: 4
Time-Series Forecasting of COVID-19 Cases Using Stacked Long Short-Term Memory Networks
Renato R. Maaliw, Zoren P. Mabunga, Frederick T. Villa
2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) (2021) Vol. 6, pp. 435-441
Closed Access | Times Cited: 9
Integrating Cyber-Physical Modeling for Pandemic Surveillance: A Graph-Based Approach for Disease Hotspot Prediction and Public Awareness
Waqas Nawaz, Muhammad Uzair, Kifayat Ullah Khan, et al.
IEICE Transactions on Information and Systems (2024) Vol. E108.D, Iss. 1, pp. 62-73
Open Access
A Novel Multi-scale Spatiotemporal Graph Neural Network for Epidemic Prediction
Zenghui Xu, Mingzhang Li, Ting Yu, et al.
Lecture notes in computer science (2024), pp. 272-287
Closed Access
Multimodality Data Fusion for COVID-19 Diagnosis
Arun Chauhan, D. N. Jagadish, Lakshman Mahto
2021 IEEE International Conference on Big Data (Big Data) (2021), pp. 4659-4666
Closed Access | Times Cited: 1
Spatiotemporal Data Engineering
Venkateswara Rao Komati
Advances in geospatial technologies book series (2023), pp. 15-62
Closed Access
Integrating EMD, LMD and TCN Methods for COVID-19 Forecasting
Lulu Sun, Zhouming Liu, Peilin Yang, et al.
Communications in computer and information science (2023), pp. 175-190
Closed Access
Improved prediction of new COVID-19 cases using a simple vector autoregressive model: Evidence from seven New York State counties
Takayoshi Kitaoka, Harutaka Takahashi
medRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access
Improved Prediction of New COVID-19 Cases Using a Simple Vector Autoregressive Model: Evidence from Seven New York State Counties
Takayoshi Kitaoka, Harutaka Takahashi
SSRN Electronic Journal (2022)
Open Access
COVID-19 Forecasting Based on Local Mean Decomposition and Temporal Convolutional Network
Lulu Sun, Zhouming Liu, Choujun Zhan, et al.
Lecture notes in computer science (2022), pp. 175-187
Closed Access
Multiwave COVID-19 Prediction via Social Awareness-Based Graph Neural Networks using Mobility and Web Search Data (preprint)
Jiawei Xue, Takahiro Yabe, Kota Tsubouchi, et al.
(2021)
Closed Access
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