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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:

Explainable Artificial Intelligence Paves the Way in Precision Diagnostics and Biomarker Discovery for the Subclass of Diabetic Retinopathy in Type 2 Diabetics
Fatma Hilal Yağın, Şeyma Yaşar, Yasin Görmez, et al.
Metabolites (2023) Vol. 13, Iss. 12, pp. 1204-1204
Open Access | Times Cited: 17

Showing 17 citing articles:

Artificial Intelligence in Point-of-Care Biosensing: Challenges and Opportunities
Connor D. Flynn, Dingran Chang
Diagnostics (2024) Vol. 14, Iss. 11, pp. 1100-1100
Open Access | Times Cited: 13
HOTGpred: Enhancing human O-linked threonine glycosylation prediction using integrated pretrained protein language model-based features and multi-stage feature selection approach
Nhat Truong Pham, Ying Zhang, Rajan Rakkiyappan, et al.
Computers in Biology and Medicine (2024) Vol. 179, pp. 108859-108859
Closed Access | Times Cited: 5
Pilot-Study to Explore Metabolic Signature of Type 2 Diabetes: A Pipeline of Tree-Based Machine Learning and Bioinformatics Techniques for Biomarkers Discovery
Fatma Hilal Yağın, Fahaid Al‐Hashem, Irshad Ahmad, et al.
Nutrients (2024) Vol. 16, Iss. 10, pp. 1537-1537
Open Access | Times Cited: 4
An improved decision tree model through hyperparameter optimization using a modified gray wolf optimization for diabetes classification
Muhammad Sam’an, Farikhin, Muhammad Munsarif
Computer Methods in Biomechanics & Biomedical Engineering (2025), pp. 1-17
Closed Access
Advancing Diabetic Retinopathy Screening: A Systematic Review of Artificial Intelligence and Optical Coherence Tomography Angiography Innovations
Alireza Hayati, Mohammad Reza Abdol Homayuni, Reza Sadeghi, et al.
Diagnostics (2025) Vol. 15, Iss. 6, pp. 737-737
Open Access
Stacking with Recursive Feature Elimination-Isolation Forest for classification of diabetes mellitus
Nur Farahaina Idris, Mohd Arfian Ismail, M. Izham Jaya, et al.
PLoS ONE (2024) Vol. 19, Iss. 5, pp. e0302595-e0302595
Open Access | Times Cited: 2
Construction and evaluation of a metabolic correlation diagnostic model for diabetes based on machine learning algorithms
Qiong Xu, Yina Zhou, Jianfen Lou, et al.
Environmental Toxicology (2024) Vol. 39, Iss. 10, pp. 4635-4648
Closed Access | Times Cited: 1
Novel approach exploring the correlation between presepsin and routine laboratory parameters using explainable artificial intelligence
Jae‐Seung Jeong, Takho Kang, Hyunsu Ju, et al.
Heliyon (2024) Vol. 10, Iss. 13, pp. e33826-e33826
Open Access | Times Cited: 1
Detection of diabetic retinopathy using artificial intelligence: an exploratory systematic review
Richard Injante, Marck Julca
LatIA (2024) Vol. 2, pp. 112-112
Closed Access | Times Cited: 1
Interpretable and explainable predictive machine learning models for data-driven protein engineering
David Medina-Ortiz, Ashkan Khalifeh, Hoda Anvari-Kazemabad, et al.
Biotechnology Advances (2024) Vol. 79, pp. 108495-108495
Open Access | Times Cited: 1
Interpretable (not just posthoc-explainable) medical claims modeling for discharge placement to reduce preventable all-cause readmissions or death
Ted L. Chang, Hongjing Xia, Sonya Mahajan, et al.
PLoS ONE (2024) Vol. 19, Iss. 5, pp. e0302871-e0302871
Open Access
Clinical applications of artificial intelligence in diabetes management: A bibliometric analysis and comprehensive review
Alfredo Daza Vergaray, Ander J. Olivos-López, Margarita Chumbirayco Pizarro, et al.
Informatics in Medicine Unlocked (2024) Vol. 50, pp. 101567-101567
Open Access
Machine learning-based identification and validation of immune-related biomarkers for early diagnosis and targeted therapy in diabetic retinopathy
Yulin Tao, Minqi Xiong, Yingchuan Peng, et al.
Gene (2024) Vol. 934, pp. 149015-149015
Closed Access
Application of Artificial Intelligence for Classification, Segmentation, Early Detection, Early Diagnosis, and Grading of Diabetic Retinopathy from Fundus Retinal Images: A Comprehensive Review
G.Kalaimathi Priya S.Rajarajeshwari, G. Chemmalar Selvi
IEEE Access (2024) Vol. 12, pp. 172499-172536
Open Access
Explainable artificial intelligence models for key-metabolites identification in overweight subjects
Isabella Mendolia, Antonino Fiannaca, Laura La Paglia, et al.
Procedia Computer Science (2024) Vol. 246, pp. 1963-1972
Open Access
Explainable Machine Learning for Efficient Diabetes Prediction Using Hyperparameter Tuning, SHAP Analysis, Partial Dependency, and LIME
Md. Manowarul Islam, Habibur Rahman Rifat, M. Shahid, et al.
Engineering Reports (2024)
Open Access
A Comparative Study of Machine Learning Algorithms Using Explainable Artificial Intelligence System for Predicting Liver Disease
A. Nilofer, S. Sasikala
Deleted Journal (2023) Vol. 01
Open Access
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