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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:

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: 45

Showing 1-25 of 45 citing articles:

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: 71
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
Modeling industrial hydrocyclone operational variables by SHAP-CatBoost - A “conscious lab” approach
Saeed Chehreh Chelgani, Hamid Nasiri, A. Tohry, et al.
Powder Technology (2023) Vol. 420, pp. 118416-118416
Open Access | Times Cited: 44
Spatiotemporal Air Pollution Forecasting in Houston-TX: A Case Study for Ozone Using Deep Graph Neural Networks
Victor Oliveira Santos, Paulo Alexandre Costa Rocha, John Scott, et al.
Atmosphere (2023) Vol. 14, Iss. 2, pp. 308-308
Open Access | Times Cited: 31
Detection of the chronic kidney disease using XGBoost classifier and explaining the influence of the attributes on the model using SHAP
Md. Johir Raihan, Md. Al-Masrur Khan, Seong‐Hoon Kee, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 30
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
Monthly sodium adsorption ratio forecasting in rivers using a dual interpretable glass-box complementary intelligent system: Hybridization of ensemble TVF-EMD-VMD, Boruta-SHAP, and eXplainable GPR
Mehdi Jamei, Mumtaz Ali, Masoud Karbasi, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121512-121512
Closed Access | Times Cited: 19
Machine learning approach to predict adsorption capacity of Fe-modified biochar for selenium
Habib Ullah, Sangar Khan, Baoliang Chen, et al.
Carbon Research (2023) Vol. 2, Iss. 1
Open Access | Times Cited: 18
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
Modeling the working pressure of a cement vertical roller mill using SHAP-XGBoost: A “conscious lab of grinding principle” approach
Rasoul Fatahi, Hadi Abdollahi, Mohammad Noaparast, et al.
Powder Technology (2025), pp. 120923-120923
Closed Access
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: 26
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
Key toxic components and sources affecting oxidative potential of atmospheric particulate matter using interpretable machine learning: Insights from fog episodes
Ruiyu Li, Caiqing Yan, Qingpeng Meng, et al.
Journal of Hazardous Materials (2023) Vol. 465, pp. 133175-133175
Closed Access | Times Cited: 14
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
Predicting the governing factors for the release of colloidal phosphorus using machine learning
Sangar Khan, Huimin Gao, Paul Milham, et al.
Chemosphere (2024) Vol. 362, pp. 142699-142699
Closed Access | Times Cited: 4
Classification of COVID-19 in Chest X-ray Images Using Fusion of Deep Features and LightGBM
Hamid Nasiri, Ghazal Kheyroddin, Morteza Dorrigiv, et al.
2022 IEEE World AI IoT Congress (AIIoT) (2022), pp. 201-206
Open Access | Times Cited: 19
PD-ADSV: An automated diagnosing system using voice signals and hard voting ensemble method for Parkinson’s disease
Paria Ghaheri, Ahmadreza Shateri, Hamid Nasiri
Software Impacts (2023) Vol. 16, pp. 100504-100504
Open Access | Times Cited: 11
Data-driven XGBoost model for maximum stress prediction of additive manufactured lattice structures
Zhiwei Zhang, Yuyan Zhang, Yintang Wen, et al.
Complex & Intelligent Systems (2023) Vol. 9, Iss. 5, pp. 5881-5892
Open Access | Times Cited: 10
Grinding Media in Ball Mills-A Review
Nyasha Matsanga, Willie Nheta, Ngonidzashe Chimwani
(2023)
Open Access | Times Cited: 10
Predictive modeling of plastic pyrolysis process for the evaluation of activation energy: Explainable artificial intelligence based comprehensive insights
Sanjeevani Hooda, Prasenjit Mondal
Journal of Environmental Management (2024) Vol. 360, pp. 121189-121189
Closed Access | Times Cited: 3
Continuous Assessment of the Environmental Impact and Economic Viability of Decarbonization Improvements in Cement Production
Olurotimi Oguntola, Steve Simske
Resources (2023) Vol. 12, Iss. 8, pp. 95-95
Open Access | Times Cited: 9
A Review on Pollution Treatment in Cement Industrial Areas: From Prevention Techniques to Python-Based Monitoring and Controlling Models
Xinghan Zhu, Jinzhong Yang, Qifei Huang, et al.
Processes (2022) Vol. 10, Iss. 12, pp. 2682-2682
Open Access | Times Cited: 15
Predicting Cost Impacts of Nonconformances in Construction Projects Using Interpretable Machine Learning
Kerim Koç, Cenk Budayan, Ömer Ekmekcioğlu, et al.
Journal of Construction Engineering and Management (2023) Vol. 150, Iss. 1
Closed Access | Times Cited: 7
Recent Applications of Explainable AI (XAI): A Systematic Literature Review
Mirka Saarela, Vili Podgorelec
Applied Sciences (2024) Vol. 14, Iss. 19, pp. 8884-8884
Open Access | Times Cited: 2
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