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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:

A Novel Approach for Feature Selection and Classification of Diabetes Mellitus: Machine Learning Methods
Roshi Saxena, Sanjay Kumar Sharma, Manali Gupta, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-11
Open Access | Times Cited: 59

Showing 1-25 of 59 citing articles:

An Ensemble Approach to Predict Early-Stage Diabetes Risk Using Machine Learning: An Empirical Study
Umm e Laila, Khalid Mahboob, Abdul Wahid Khan, et al.
Sensors (2022) Vol. 22, Iss. 14, pp. 5247-5247
Open Access | Times Cited: 99
Application of Machine Learning Models for Early Detection and Accurate Classification of Type 2 Diabetes
Orlando Iparraguirre-Villanueva, Karina Espinola-Linares, Rosalynn Ornella Flores-Castañeda, et al.
Diagnostics (2023) Vol. 13, Iss. 14, pp. 2383-2383
Open Access | Times Cited: 39
Prediction of Diabetes Using Data Mining and Machine Learning Algorithms: A Cross-Sectional Study
Hassan Shojaee-Mend, Farnia Velayati, Batool Tayefi, et al.
Healthcare Informatics Research (2024) Vol. 30, Iss. 1, pp. 73-82
Open Access | Times Cited: 5
Optimizing diabetes classification with a machine learning-based framework
Xin Feng, Yihuai Cai, Ruihao Xin
BMC Bioinformatics (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 12
A New Approach of Hybrid Sampling SMOTE and ENN to the Accuracy of Machine Learning Methods on Unbalanced Diabetes Disease Data
Hairani Hairani, Dadang Priyanto
International Journal of Advanced Computer Science and Applications (2023) Vol. 14, Iss. 8
Open Access | Times Cited: 11
Machine Learning Approach to Metabolomic Data Predicts Type 2 Diabetes Mellitus Incidence
Andreas Leiherer, Axel Muendlein, Sylvia Mink, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 10, pp. 5331-5331
Open Access | Times Cited: 4
Research Progress and Prospects of Intelligent Diabetes Monitoring Systems: A Review
Yuanyuan Zou, Zhengkang Chu, Tongyan Yang, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 15, pp. 23401-23435
Closed Access | Times Cited: 4
REMED-T2D: A robust ensemble learning model for early detection of type 2 diabetes using healthcare dataset
Le Thi Phan, Rajan Rakkiyappan, Balachandran Manavalan
Computers in Biology and Medicine (2025) Vol. 187, pp. 109771-109771
Closed Access
Performance Comparison of Different Machine Learning Classifiers for Diabetes Prediction
Dipayan Ghosh, Auroop R. Ganguly, Rounak Chakraborty, et al.
Lecture notes in networks and systems (2025), pp. 127-141
Closed Access
Enhancing Deep Neural Network Performance in Diabetes Classification: A Hybrid Optimization Approach with Kernel Similarity
Sudipta Priyadarshinee, Madhumita Panda
SN Computer Science (2025) Vol. 6, Iss. 4
Closed Access
Feature selection using Hybridized Genghis Khan Shark with Snow Ablation optimization technique for Multi-Disease Prognosis
Ruqsar Zaitoon, Shaik Salma Asiya Begum, Sachi Nandan Mohanty, et al.
Intelligence-Based Medicine (2025), pp. 100249-100249
Open Access
Impact of machine learning-based imputation techniques on medical datasets- a comparative analysis
Shweta Tiwaskar, Mamoon Rashid, Prasad Gokhale
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 3
Chronic Diseases Prediction Using Machine Learning With Data Preprocessing Handling: A Critical Review
Nur Ghaniaviyanto Ramadhan, Adiwijaya Adiwijaya, Warih Maharani, et al.
IEEE Access (2024) Vol. 12, pp. 80698-80730
Open Access | Times Cited: 3
Exploring Hyper-Parameters and Feature Selection for Predicting Non-Communicable Chronic Disease Using Stacking Classifier
Pooja Yadav, S. C. Sharma, Rajesh Mahadeva, et al.
IEEE Access (2023) Vol. 11, pp. 80030-80055
Open Access | Times Cited: 9
Strong convergence of a modified extragradient algorithm to solve pseudomonotone equilibrium and application to classification of diabetes mellitus
Watcharaporn Cholamjiak, Raweerote Suparatulatorn
Chaos Solitons & Fractals (2023) Vol. 168, pp. 113108-113108
Closed Access | Times Cited: 8
Improved Diabetes Prediction with Reduced Feature Sets: Evaluating Feature Selection Techniques in Machine Learning
Soumik Datta, S. M. Mahedy Hasan, Md. Farukuzzaman Faruk, et al.
(2023), pp. 104-108
Closed Access | Times Cited: 8
Tabular Data Generation to Improve Classification of Liver Disease Diagnosis
Mohammad Alauthman, Amjad Aldweesh, Ahmad Al–Qerem, et al.
Applied Sciences (2023) Vol. 13, Iss. 4, pp. 2678-2678
Open Access | Times Cited: 7
Diabetes Prediction Using Bi-directional Long Short-Term Memory
Sushma Jaiswal, Priyanka Gupta
SN Computer Science (2023) Vol. 4, Iss. 4
Closed Access | Times Cited: 7
Integrating Innovation in Healthcare: The Evolution of “CURA’s” AI-Driven Virtual Wards for Enhanced Diabetes and Kidney Disease Monitoring
Mohammed Aljaafari, Shorouk E. El-deep, Amr A. Abohany, et al.
IEEE Access (2024) Vol. 12, pp. 126389-126414
Open Access | Times Cited: 2
Federated learning-based disease prediction: A fusion approach with feature selection and extraction
Ramdas Kapila, Sumalatha Saleti
Biomedical Signal Processing and Control (2024) Vol. 100, pp. 106961-106961
Closed Access | Times Cited: 2
The Exploring feature selection techniques on Classification Algorithms for Predicting Type 2 Diabetes at Early Stage
Mila Desi Anasanti, Khairunisa Hilyati, Annisa Novtariany
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) (2022) Vol. 6, Iss. 5, pp. 832-839
Open Access | Times Cited: 10
Integrative analysis of Mendelian randomization and gene expression profiles reveals a null causal relationship between adiponectin and diabetic retinopathy
Ao Zhang, Hui Wu, Chi Wang, et al.
Adipocyte (2023) Vol. 12, Iss. 1
Open Access | Times Cited: 4
Identifying diagnostic indicators for type 2 diabetes mellitus from physical examination using interpretable machine learning approach
Xiang Lv, Jiesi Luo, Wei Huang, et al.
Frontiers in Endocrinology (2024) Vol. 15
Open Access | Times Cited: 1
Optimized Neural Networks for Diabetes Classification Using Pima Indians Diabetes Database
Ahmed F. Ashour, Mostafa M. Fouda, Zubair Md. Fadlullah, et al.
(2024), pp. 1-7
Closed Access | Times Cited: 1
Analyzing Machine Learning Approaches for Diabetes Risk Prediction: Comparative Performance Assessment Using BRFSS Data
Simeon Yuda Prasetyo, Zahra Nabila Izdihar, Ghinaa Zain Nabiilah
(2024), pp. 324-329
Closed Access | Times Cited: 1
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