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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:

Breast Cancer Prediction Analysis using Machine Learning Algorithms
Vinayak A. Telsang, Kavyashree Hegde
(2020), pp. 1-5
Closed Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Performance Analysis of XGBoost Ensemble Methods for Survivability with the Classification of Breast Cancer
T R Mahesh, V. Vinoth Kumar, V. Muthukumaran, et al.
Journal of Sensors (2022) Vol. 2022, pp. 1-8
Open Access | Times Cited: 49
Early predictive model for breast cancer classification using blended ensemble learning
T R Mahesh, V. Vinoth Kumar, V Vivek, et al.
International Journal of Systems Assurance Engineering and Management (2022) Vol. 15, Iss. 1, pp. 188-197
Closed Access | Times Cited: 48
An integrative machine learning framework for classifying SEER breast cancer
P. Manikandan, U. Durga, C Ponnuraja
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 24
A quantum-optimized approach for breast cancer detection using SqueezeNet-SVM
Anas Bilal, Ali Alkhathlan, Faris Kateb, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Predicting breast cancer recurrence using deep learning
Deepa Kumari, M. Naidu, Subhrakanta Panda, et al.
Deleted Journal (2025) Vol. 7, Iss. 2
Open Access
Breast Cancer Detection: An Effective Analysis of Different ML Models with Resampling Technique
Alongbar Wary, D. Suri, Jaayasi Mangla, et al.
Lecture notes in networks and systems (2025), pp. 217-225
Closed Access
Machine Learning Based Expert System for Breast Cancer Prediction (MLESBCP)
Akhil Das, Saroj Kumar Biswas, Arup K. Mandal, et al.
Communications in computer and information science (2025), pp. 275-286
Closed Access
Deep Learning Paradigms for Breast Cancer Diagnosis: A Comparative Study on Wisconsin Diagnostic Dataset
Akinul Islam Jony, Arjun Kumar Bose Arnob
Malaysian Journal of Science and Advanced Technology (2024), pp. 109-117
Open Access | Times Cited: 4
Predicting Breast Cancer Risk from Histopathology Images using Hybrid Deep Learning Classifier
G. Sajiv, G. Ramkumar, S. Shanthi, et al.
Medical Engineering & Physics (2024), pp. 104149-104149
Closed Access | Times Cited: 3
Enhancing Breast Cancer Detection: A Machine Learning Approach for Early Diagnosis and Classification
Aditi Sawant, Divya Patil, Dimple Khuman, et al.
2022 9th International Conference on Computing for Sustainable Global Development (INDIACom) (2024), pp. 235-239
Closed Access | Times Cited: 3
A Deep-Learning-Based Novel Method to Classify Breast Cancer
Soham Saha, Ahona Dutta, Sabarna Choudhury
(2024), pp. 503-508
Closed Access | Times Cited: 2
Performance Comparison of Different Machine Learning Techniques for Early Prediction of Breast Cancer using Wisconsin Breast Cancer Dataset
Atajan Rovshenov, Serhat Peker
(2022)
Closed Access | Times Cited: 11
Machine Learning Approach for Breast Cancer Prediction: A Review
Yash Wankhade, Shrividya Toutam, Khushboo Thakre, et al.
(2023), pp. 566-570
Closed Access | Times Cited: 5
Unlocking the Potential Thorough Analysis of Machine Learning for Breast Cancer Diagnosis
P. Bhaskar, Tahaseen Syed, Hima Varsha Daka, et al.
International Journal of Innovative Science and Research Technology (IJISRT) (2024), pp. 745-750
Open Access | Times Cited: 1
Breast Cancer Detection Using Machine Learning Algorithms
Samer Hamed, Abdelwadood Mesleh, Abdullah Arabiyyat
International Journal of Computer Science and Mobile Computing (2021) Vol. 10, Iss. 11, pp. 4-11
Open Access | Times Cited: 12
Breast cancer diagnosis and management guided by data augmentation, utilizing an integrated framework of SHAP and random augmentation
Chukwuebuka Joseph Ejiyi, Zhen Qin, Happy Nkanta Monday, et al.
BioFactors (2023) Vol. 50, Iss. 1, pp. 114-134
Closed Access | Times Cited: 4
Prediction of Breast Cancer based on Various Medical Symptoms Using Machine Learning Algorithms
Mayank Agrawal, Vinod Jain
2022 6th International Conference on Trends in Electronics and Informatics (ICOEI) (2022), pp. 1242-1245
Closed Access | Times Cited: 7
Breast Cancer-Risk Factors and Prediction Using Machine-Learning Algorithms and Data Source: A Review of Literature
Ayman Alsabry, Malek Algabri, Amin Mohamed Ahsan
مجلة جامعة صنعاء للعلوم التطبيقية والتكنولوجيا (2023) Vol. 1, Iss. 2
Open Access | Times Cited: 3
Breast Cancer Diagnosis Using a Novel Parallel Support Vector Machine with Harris Hawks Optimization
Sultan Almotairi, Elsayed Badr, Mustafa Abdul Salam, et al.
Mathematics (2023) Vol. 11, Iss. 14, pp. 3251-3251
Open Access | Times Cited: 3
Breast Cancer Prediction using Optimized Machine Learning Classifiers and Data Balancing Techniques
Saniya Anklesaria, Unnati Maheshwari, Ria Lele, et al.
2022 6th International Conference On Computing, Communication, Control And Automation (ICCUBEA (2022), pp. 1-7
Closed Access | Times Cited: 5
Breast Histopathology Image Classification: A Comparative Evaluation of SVM, Random Forest and CNN
Yogitha, P Rachana, M Milina, et al.
(2023), pp. 1-6
Closed Access | Times Cited: 2
Breast Cancer Detection: SVM and SMOTE Integration for Fine Needle Aspiration Feature Analysis
Prabira Kumar Sethy, S. Shanthi, Manas Panigrahi, et al.
(2024), pp. 1-4
Closed Access
Comprehensive Analysis of Machine and Deep Learning Models for Breast Cancer Diagnosis and Risk Assessment with Diverse Datasets
Rajon Dash, Md. Saidur Rahman Kohinoor, Promise Ghosh Chowdhury
(2024), pp. 1-7
Closed Access
Breast Cancer Prediction Using Different Machine Learning Algorithm
Ujwala Ravale, Yashashree Bendale
Advances in intelligent systems and computing (2023), pp. 493-502
Closed Access | Times Cited: 1
Bio-Inspired Optimization Technique for Feature Selection to Enhance Accuracy of BC Detection
V. Kalaiyarasi, Meenakshi Meenakshi, Sanjay Jain, et al.
2022 International Conference on Inventive Computation Technologies (ICICT) (2023), pp. 741-748
Closed Access | Times Cited: 1
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