Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Phenomapping of Patients with Primary Breast Cancer Using Machine Learning-Based Unsupervised Cluster Analysis
Sara Ferro, Daniele Bottigliengo, Darío Gregori, et al.
Journal of Personalized Medicine (2021) Vol. 11, Iss. 4, pp. 272-272
Open Access | Times Cited: 17

Showing 17 citing articles:

Machine Learning Methods for Small Data Challenges in Molecular Science
Bozheng Dou, Zailiang Zhu, Ekaterina Merkurjev, et al.
Chemical Reviews (2023) Vol. 123, Iss. 13, pp. 8736-8780
Open Access | Times Cited: 170
A Comprehensive Review of Artificial Intelligence Approaches in Omics Data Processing: Evaluating Progress and Challenges
Ali Mahmoud Ali, Mazin Abed Mohammed
International Journal of Mathematics Statistics and Computer Science (2023) Vol. 2, pp. 114-167
Open Access | Times Cited: 35
Vitamin D Deficiency in Women with Breast Cancer: A Correlation with Osteoporosis? A Machine Learning Approach with Multiple Factor Analysis
Alessandro de Sire, Luca Gallelli, Nicola Marotta, et al.
Nutrients (2022) Vol. 14, Iss. 8, pp. 1586-1586
Open Access | Times Cited: 19
Halal Supply Chain Risk using Unsupervised Learning Methods for Clustering Leather Industries
Rahmad Kurniawan, Fitra Lestari, Mawardi Mawardi, et al.
International Journal of Computing and Digital Systems (2024) Vol. 15, Iss. 1, pp. 899-910
Open Access | Times Cited: 2
A new survival analysis model in adjuvant Tamoxifen-treated breast cancer patients using manifold-based semi-supervised learning
Ramazan Teimouri Yansari, Mitra Mirzarezaee, Mehdi Sadeghi, et al.
Journal of Computational Science (2022) Vol. 61, pp. 101645-101645
Closed Access | Times Cited: 12
Cyclin A2 and Ki-67 proliferation markers could be used to identify tumors with poor prognosis in African American women with breast cancer
Desta Beyene, Tammey Naab, Victor Apprey, et al.
Journal of Cancer Biology (2023) Vol. 4, Iss. 1
Open Access | Times Cited: 5
Exploring the State of Machine Learning and Deep Learning in Medicine: A Survey of Italian Research Community
Alessio Bottrighi, Marzio Pennisi
(2023)
Open Access | Times Cited: 3
Exploring the State of Machine Learning and Deep Learning in Medicine: A Survey of the Italian Research Community
Alessio Bottrighi, Marzio Pennisi
Information (2023) Vol. 14, Iss. 9, pp. 513-513
Open Access | Times Cited: 3
Unique clusters of patterns of breast cancer survivorship
Hilary I. Okagbue, Pelumi E. Oguntunde, Patience I. Adamu, et al.
Health and Technology (2022) Vol. 12, Iss. 2, pp. 365-384
Closed Access | Times Cited: 5
The Circular RNA Circ_0085494 Regulates Prostate Cancer Progression Through NRBP1/miR-497-5p Axis
Chunhui Cao, Guanghai Sun, Keping Le, et al.
Biochemical Genetics (2023) Vol. 61, Iss. 5, pp. 1775-1790
Closed Access | Times Cited: 2
Machine Learning Based Ensemble Classifier using Wisconsin Dataset For Breast Cancer Prediction
G S Pradeep Ghantasala, Anjaneyulu Kunchala, R. Sathiyaraj, et al.
(2023)
Closed Access | Times Cited: 2
Unsupervized Techniques to Identify Patterns in Gynecologic Information
Marco Chacaguasay, Ruth Reátegui, Priscila Valdiviezo-Díaz, et al.
Communications in computer and information science (2024), pp. 31-43
Closed Access
Imputing Missing Data in One-Shot Devices Using Unsupervised Learning Approach
Hon Yiu So, Man Ho Ling, N. Balakrishnan
Mathematics (2024) Vol. 12, Iss. 18, pp. 2884-2884
Open Access
Prediction of breast cancer aggression-related genetic markers based on weighted gene co-expression network analysis
Yongqi Su, Ling Guo, Fan Pan
International Conference on Biomedical and Intelligent Systems (IC-BIS 2022) (2022), pp. 142-142
Closed Access | Times Cited: 1
Machine learning techniques to identify patterns in gynecologic information
Marco Chacaguasay, Ruth Reátegui, Priscila Valdiviezo-Díaz, et al.
Research Square (Research Square) (2023)
Open Access
Identification of Key Genes in Breast Cancer by Gene Co-expression Network Analysis and Betweeness Centrality
Fan Pan, Ling Guo, Minghua Liu, et al.
(2023), pp. 6806-6810
Closed Access
Revealing the Environmental Characteristics of Towns in the Middle Himalayas Using a Geographic Information System and Self-Organizing Map
Aike Kan, Qing Xiang, Yang Xiao, et al.
Sustainability (2023) Vol. 15, Iss. 20, pp. 15110-15110
Open Access
Page 1

Scroll to top