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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:

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

Showing 1-25 of 72 citing articles:

Hyperparameter Optimizer with Deep Learning-Based Decision-Support Systems for Histopathological Breast Cancer Diagnosis
Marwa Obayya, Mashael Maashi, Nadhem Nemri, et al.
Cancers (2023) Vol. 15, Iss. 3, pp. 885-885
Open Access | Times Cited: 51
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
Advancements and Prospects of Machine Learning in Medical Diagnostics: Unveiling the Future of Diagnostic Precision
Sohaib Asif, Wenhui Yi, Saif Ur-Rehman, et al.
Archives of Computational Methods in Engineering (2024)
Closed Access | Times Cited: 17
MobileNet-SVM: A Lightweight Deep Transfer Learning Model to Diagnose BCH Scans for IoMT-Based Imaging Sensors
Roseline Oluwaseun Ogundokun, Sanjay Misra, Akinyemi Omololu Akinrotimi, et al.
Sensors (2023) Vol. 23, Iss. 2, pp. 656-656
Open Access | Times Cited: 35
Unveiling the future of breast cancer assessment: a critical review on generative adversarial networks in elastography ultrasound
Mohammed Yusuf Ansari, Marwa Qaraqe, Raffaella Righetti, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 25
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
ETECADx: Ensemble Self-Attention Transformer Encoder for Breast Cancer Diagnosis Using Full-Field Digital X-ray Breast Images
Aymen M. Al-Hejri, Riyadh M. Al-Tam, Muneer Fazea, et al.
Diagnostics (2022) Vol. 13, Iss. 1, pp. 89-89
Open Access | Times Cited: 29
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
Accuracy Analysis of Deep Learning Methods in Breast Cancer Classification: A Structured Review
Marina Yusoff, Toto Haryanto, Heru Suhartanto, et al.
Diagnostics (2023) Vol. 13, Iss. 4, pp. 683-683
Open Access | Times Cited: 20
Adaptive Threshold Learning in Frequency Domain for Classification of Breast Cancer Histopathological Images
Yujian Liu, Xiaozhang Liu, Yuan Qi
International Journal of Intelligent Systems (2024) Vol. 2024, pp. 1-13
Open Access | Times Cited: 6
LightGBM: A Leading Force in Breast Cancer Diagnosis Through Machine Learning and Image Processing
Bassam M. Kanber, Ahmad Al Smadi, Naglaa F. Noaman, et al.
IEEE Access (2024) Vol. 12, pp. 39811-39832
Open Access | Times Cited: 6
Advances of AI in image-based computer-aided diagnosis: A review
Mst. Nilufa Yeasmin, Md Al Amin, Tasmim Jamal Joti, et al.
Array (2024) Vol. 23, pp. 100357-100357
Open Access | Times Cited: 6
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 Novel Approach for Production Allocation in Multi-Layer Oil Reservoirs Based on Machine Learning Combining Game Theory
Tianru Song, Weiyao Zhu, Qiang Chen, et al.
Geoenergy Science and Engineering (2025), pp. 213706-213706
Closed Access
Cosine Additive Angular Margin Loss for Breast Cancer Classification in Histopathological Images with Small AI Systems
Pendar Alirezazadeh, Fadi Dornaika, Abdelmalik Moujahid
ACM Transactions on Intelligent Systems and Technology (2025)
Closed Access
Classifying breast intraductal proliferative lesions via a knowledge distillation framework using convolutional neural network-based nuclei-segmentation-assisted classification (KDCNN-NSAC)
Xiangmin Li, Jiamei Chen, Bo Luo, et al.
Heliyon (2025), pp. e42756-e42756
Open Access
Adaptive Fusion Attention for enhanced classification and interpretability in medical imaging
Nagur Shareef Shaik, N. Veeranjaneulu, Jyostna Devi Bodapati
Machine Vision and Applications (2025) Vol. 36, Iss. 3
Closed Access
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
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
LitefusionNet: Boosting the performance for medical image classification with an intelligent and lightweight feature fusion network
Sohaib Asif, Q Ul Ain, Raeed Al-Sabri, et al.
Journal of Computational Science (2024) Vol. 80, pp. 102324-102324
Closed Access | Times Cited: 4
Advancing cancer diagnosis and prognostication through deep learning mastery in breast, colon, and lung histopathology with ResoMergeNet
Chukwuebuka Joseph Ejiyi, Zhen Qin, Victor Kwaku Agbesi, et al.
Computers in Biology and Medicine (2024) Vol. 185, pp. 109494-109494
Closed Access | Times Cited: 4
Impact of Image Preprocessing Methods and Deep Learning Models for Classifying Histopathological Breast Cancer Images
David Murcia-Gómez, Ignacio Rojas-Valenzuela, Olga Valenzuela
Applied Sciences (2022) Vol. 12, Iss. 22, pp. 11375-11375
Open Access | Times Cited: 21
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
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