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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:

Artificial Intelligence for Forecasting the Prevalence of COVID-19 Pandemic: An Overview
Ammar H. Elsheikh, Amal I. Saba, Hitesh Panchal, et al.
Healthcare (2021) Vol. 9, Iss. 12, pp. 1614-1614
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

A new optimized artificial neural network model to predict thermal efficiency and water yield of tubular solar still
Essam B. Moustafa, Ahmed H. Hammad, Ammar H. Elsheikh
Case Studies in Thermal Engineering (2021) Vol. 30, pp. 101750-101750
Open Access | Times Cited: 141
Applications of machine learning in friction stir welding: Prediction of joint properties, real-time control and tool failure diagnosis
Ammar H. Elsheikh
Engineering Applications of Artificial Intelligence (2023) Vol. 121, pp. 105961-105961
Closed Access | Times Cited: 135
Predicting Characteristics of Dissimilar Laser Welded Polymeric Joints Using a Multi-Layer Perceptrons Model Coupled with Archimedes Optimizer
Essam B. Moustafa, Ammar H. Elsheikh
Polymers (2023) Vol. 15, Iss. 1, pp. 233-233
Open Access | Times Cited: 95
A coupled artificial neural network with artificial rabbits optimizer for predicting water productivity of different designs of solar stills
Abdulmohsen Alsaiari, Essam B. Moustafa, Hesham Alhumade, et al.
Advances in Engineering Software (2022) Vol. 175, pp. 103315-103315
Closed Access | Times Cited: 88
Predicting kerf quality characteristics in laser cutting of basalt fibers reinforced polymer composites using neural network and chimp optimization
I.M.R. Najjar, A.M. Sadoun, Mohamed Abd Elaziz, et al.
Alexandria Engineering Journal (2022) Vol. 61, Iss. 12, pp. 11005-11018
Open Access | Times Cited: 86
Forecasting the strength of graphene nanoparticles-reinforced cementitious composites using ensemble learning algorithms
Majid Khan, Roz‐Ud‐Din Nassar, Waqar Anwar, et al.
Results in Engineering (2024) Vol. 21, pp. 101837-101837
Open Access | Times Cited: 27
Application of Machine Learning Approaches to Predict the Strength Property of Geopolymer Concrete
Rongchuan Cao, Zheng Fang, Man Jin, et al.
Materials (2022) Vol. 15, Iss. 7, pp. 2400-2400
Open Access | Times Cited: 40
A Comparative Analysis of Machine Learning Models: A Case Study in Predicting Chronic Kidney Disease
Hasnain Iftikhar, Murad Khan, Zardad Khan, et al.
Sustainability (2023) Vol. 15, Iss. 3, pp. 2754-2754
Open Access | Times Cited: 35
Kerf characteristics during CO2 laser cutting of polymeric materials: Experimental investigation and machine learning-based prediction
Abdulsalam M. Alhawsawi, Essam B. Moustafa, Manabu Fujii, et al.
Engineering Science and Technology an International Journal (2023) Vol. 46, pp. 101519-101519
Open Access | Times Cited: 32
Compressive strength prediction of concrete blended with carbon nanotubes using gene expression programming and random forest: hyper-tuning and optimization
Dawei Yang, Ping Xu, Athar Zaman, et al.
Journal of Materials Research and Technology (2023) Vol. 24, pp. 7198-7218
Open Access | Times Cited: 30
Automated System for Identifying COVID-19 Infections in Computed Tomography Images Using Deep Learning Models
Karrar Hameed Abdulkareem, Salama A. Mostafa, Zainab N. Al-Qudsy, et al.
Journal of Healthcare Engineering (2022) Vol. 2022, pp. 1-13
Open Access | Times Cited: 34
Laser machining sapphire via Si-sapphire interface absorption and process optimization using an integrated approach of the Taguchi method with grey relational analysis
Ali Naderi, Yongling Wu, Liyong Wang, et al.
Journal of Materials Research and Technology (2023) Vol. 24, pp. 663-674
Open Access | Times Cited: 16
Advancing Fatigue Life Prediction with Machine Learning: A review
Atef Hamada, Shaimaa Elyamny, Walaa Abd‐Elaziem, et al.
Materials Today Communications (2025), pp. 111525-111525
Closed Access
Wide-Scope Target and Suspect Screening of Antibiotics in Effluent Wastewater from Wastewater Treatment Plants in Europe
Kelsey Ng, ‪Nikiforos Alygizakis, Νikolaos S. Τhomaidis, et al.
Antibiotics (2023) Vol. 12, Iss. 1, pp. 100-100
Open Access | Times Cited: 14
Artificial Intelligence for Smart Manufacturing in Industry 5.0: Methods, Applications, and Challenges
Huu Du Nguyen, Kim Phuc Tran
Springer series in reliability engineering (2023), pp. 5-33
Closed Access | Times Cited: 13
Forecasting the spread of COVID-19 based on policy, vaccination, and Omicron data
Kyulhee Han, Bogyeom Lee, Doeun Lee, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
OptiSembleForecasting: optimization-based ensemble forecasting using MCS algorithm and PCA-based error index
Md Yeasin, Ranjit Kumar Paul
The Journal of Supercomputing (2023) Vol. 80, Iss. 2, pp. 1568-1597
Closed Access | Times Cited: 11
Machine Learning to Rate and Predict the Efficiency of Waterflooding for Oil Production
Ivan Makhotin, Denis Orlov, Dmitry Koroteev
Energies (2022) Vol. 15, Iss. 3, pp. 1199-1199
Open Access | Times Cited: 17
Mathematical modeling and analysis of the SARS-Cov-2 disease with reinfection
Atifa Asghar, Muhammad Altaf Khan, Kulpash Iskakova, et al.
Computational Biology and Chemistry (2022) Vol. 98, pp. 107678-107678
Open Access | Times Cited: 17
Evolution of Antimicrobial Susceptibility to Penicillin in Invasive Strains of Streptococcus pneumoniae during 2007–2021 in Madrid, Spain
Sara de Miguel, Marta Pérez-Abeledo, Belén Ramos, et al.
Antibiotics (2023) Vol. 12, Iss. 2, pp. 289-289
Open Access | Times Cited: 9
COVID-19 seroprevalence estimation and forecasting in the USA from ensemble machine learning models using a stacking strategy
Gontzal Sagastabeitia, Josu Doncel, José Aguilar, et al.
Expert Systems with Applications (2024) Vol. 258, pp. 124930-124930
Open Access | Times Cited: 2
Artificial Intelligence Applied to Improve Scientific Reviews: The Antibacterial Activity of Cistus Plants as Proof of Concept
Francisco Javier Álvarez‐Martínez, Fernando Borrás, Vicente Micol, et al.
Antibiotics (2023) Vol. 12, Iss. 2, pp. 327-327
Open Access | Times Cited: 6
SVM-RFE enabled feature selection with DMN based centroid update model for incremental data clustering using COVID-19
M. Robinson Joel, G. Manikandan, G. Bhuvaneswari, et al.
Computer Methods in Biomechanics & Biomedical Engineering (2023) Vol. 27, Iss. 10, pp. 1224-1238
Closed Access | Times Cited: 5
Grid Distribution Fault Occurrence and Remedial Measures Prediction/Forecasting through Different Deep Learning Neural Networks by Using Real Time Data from Tabuk City Power Grid
Fahad M. Almasoudi
Energies (2023) Vol. 16, Iss. 3, pp. 1026-1026
Open Access | Times Cited: 4
Predicting the Spread of a Pandemic Using Machine Learning: A Case Study of COVID-19 in the UAE
Donthi Sankalpa, Salam Dhou, Michel Pasquier, et al.
Applied Sciences (2024) Vol. 14, Iss. 10, pp. 4022-4022
Open Access | Times Cited: 1
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