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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:

Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoost
Hamid Nasiri, Sharif Hasani
Radiography (2022) Vol. 28, Iss. 3, pp. 732-738
Open Access | Times Cited: 88

Showing 1-25 of 88 citing articles:

A Novel Framework Based on Deep Learning and ANOVA Feature Selection Method for Diagnosis of COVID-19 Cases from Chest X-Ray Images
Hamid Nasiri, Seyed Ali Alavi
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-11
Open Access | Times Cited: 75
Classification of Breast Tumors Based on Histopathology Images Using Deep Features and Ensemble of Gradient Boosting Methods
Mohammad Reza Abbasniya, Sayed Ali Sheikholeslamzadeh, Hamid Nasiri, et al.
Computers & Electrical Engineering (2022) Vol. 103, pp. 108382-108382
Closed Access | Times Cited: 72
Automated detection and forecasting of COVID-19 using deep learning techniques: A review
Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari, et al.
Neurocomputing (2024) Vol. 577, pp. 127317-127317
Open Access | Times Cited: 49
Breast cancer diagnosis from histopathology images using deep neural network and XGBoost
Alireza Maleki, Mohammad Raahemi, Hamid Nasiri
Biomedical Signal Processing and Control (2023) Vol. 86, pp. 105152-105152
Closed Access | Times Cited: 47
Reinforced Collaborative-Competitive Representation for Biomedical Image Recognition
Junwei Jin, S. Kevin Zhou, Yanting Li, et al.
Interdisciplinary Sciences Computational Life Sciences (2025)
Closed Access | Times Cited: 1
Interpretable modeling of metallurgical responses for an industrial coal column flotation circuit by XGBoost and SHAP-A “conscious-lab” development
Saeed Chehreh Chelgani, Hamid Nasiri, Mehdi Alidokht
International Journal of Mining Science and Technology (2021) Vol. 31, Iss. 6, pp. 1135-1144
Open Access | Times Cited: 67
Modeling of energy consumption factors for an industrial cement vertical roller mill by SHAP-XGBoost: a "conscious lab" approach
Rasoul Fatahi, Hamid Nasiri, Ehsan Dadfar, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 46
RADIC:A tool for diagnosing COVID-19 from chest CT and X-ray scans using deep learning and quad-radiomics
Omneya Attallah
Chemometrics and Intelligent Laboratory Systems (2023) Vol. 233, pp. 104750-104750
Open Access | Times Cited: 36
Chest X-ray in Emergency Radiology: What Artificial Intelligence Applications Are Available?
Giovanni Irmici, Maurizio Cè, Elena Caloro, et al.
Diagnostics (2023) Vol. 13, Iss. 2, pp. 216-216
Open Access | Times Cited: 30
Joint Diagnosis of Pneumonia, COVID-19, and Tuberculosis from Chest X-ray Images: A Deep Learning Approach
Mohammed Salih Ahmed, Atta Rahman, Faris AlGhamdi, et al.
Diagnostics (2023) Vol. 13, Iss. 15, pp. 2562-2562
Open Access | Times Cited: 30
SCovNet: A skip connection-based feature union deep learning technique with statistical approach analysis for the detection of COVID-19
Kiran Kumar Patro, Allam Jaya Prakash, Mohamed Hammad, et al.
Journal of Applied Biomedicine (2023) Vol. 43, Iss. 1, pp. 352-368
Open Access | Times Cited: 27
Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
Kashif Shaheed, Piotr Szczuko, Qaisar Abbas, et al.
Healthcare (2023) Vol. 11, Iss. 6, pp. 837-837
Open Access | Times Cited: 24
Detection of Monkeypox Cases Based on Symptoms Using XGBoost and Shapley Additive Explanations Methods
Alireza Farzipour, Roya Elmi, Hamid Nasiri
Diagnostics (2023) Vol. 13, Iss. 14, pp. 2391-2391
Open Access | Times Cited: 23
An emperor penguin optimizer application for medical diagnostics
Luka Jovanovic, Miodrag Živković, Miloš Antonijević, et al.
(2022)
Closed Access | Times Cited: 36
Modeling operational cement rotary kiln variables with explainable artificial intelligence methods – a “conscious lab” development
Rasoul Fatahi, Hamid Nasiri, Arman Homafar, et al.
Particulate Science And Technology (2022) Vol. 41, Iss. 5, pp. 715-724
Open Access | Times Cited: 27
Machine Learning Augmented Interpretation of Chest X-rays: A Systematic Review
Hassan K. Ahmad, Michael Milne, Quinlan D. Buchlak, et al.
Diagnostics (2023) Vol. 13, Iss. 4, pp. 743-743
Open Access | Times Cited: 16
CatBoost-SHAP for modeling industrial operational flotation variables – A “conscious lab” approach
Saeed Chehreh Chelgani, Arman Homafar, Hamid Nasiri, et al.
Minerals Engineering (2024) Vol. 213, pp. 108754-108754
Open Access | Times Cited: 5
A short review of radiation-induced degradation of III–V photovoltaic cells for space applications
José Maurilio Raya-Armenta, Najmeh Bazmohammadi, Juan C. Vásquez, et al.
Solar Energy Materials and Solar Cells (2021) Vol. 233, pp. 111379-111379
Open Access | Times Cited: 33
COVID-19 Detection from Chest X-rays Using Trained Output Based Transfer Learning Approach
Sanjay Kumar, Abhishek Mallik
Neural Processing Letters (2022) Vol. 55, Iss. 3, pp. 2405-2428
Open Access | Times Cited: 27
Deep Learning Techniques for COVID-19 Detection Based on Chest X-ray and CT-scan Images: A Short Review and Future Perspective
Maad M. Mijwil, Karan Aggarwal, Ruchi Doshi, et al.
Asian Journal of Applied Sciences (2022) Vol. 10, Iss. 3
Open Access | Times Cited: 24
Modeling coking coal indexes by SHAP-XGBoost: Explainable artificial intelligence method
Arman Homafar, Hamid Nasiri, Saeed Chehreh Chelgani
Fuel Communications (2022) Vol. 13, pp. 100078-100078
Closed Access | Times Cited: 24
Diagnosis of Parkinson’s disease based on voice signals using SHAP and hard voting ensemble method
Paria Ghaheri, Hamid Nasiri, Ahmadreza Shateri, et al.
Computer Methods in Biomechanics & Biomedical Engineering (2023) Vol. 27, Iss. 13, pp. 1858-1874
Open Access | Times Cited: 14
Multifactor data analysis to forecast an individual's severity over novel COVID‐19 pandemic using extreme gradient boosting and random forest classifier algorithms
Ganesh Yenurkar, Sandip Mal, Vincent Omollo Nyangaresi, et al.
Engineering Reports (2023) Vol. 5, Iss. 12
Open Access | Times Cited: 13
Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome
Fatma Hilal Yağın, Ahmadreza Shateri, Hamid Nasiri, et al.
PeerJ Computer Science (2024) Vol. 10, pp. e1857-e1857
Open Access | Times Cited: 4
Machine learning for fatigue lifetime predictions in 3D-printed polylactic acid biomaterials based on interpretable extreme gradient boosting model
Hamid Nasiri, Ali Dadashi, Mohammad Azadi
Materials Today Communications (2024) Vol. 39, pp. 109054-109054
Closed Access | Times Cited: 4
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