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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:

Predicting the Risk of Incident Type 2 Diabetes Mellitus in Chinese Elderly Using Machine Learning Techniques
Qing Liu, Miao Zhang, Yifeng He, et al.
Journal of Personalized Medicine (2022) Vol. 12, Iss. 6, pp. 905-905
Open Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

Predicting diabetes in adults: identifying important features in unbalanced data over a 5-year cohort study using machine learning algorithm
Maryam Talebi Moghaddam, Yunes Jahani, Zahra Arefzadeh, et al.
BMC Medical Research Methodology (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 7
Diabetic peripheral neuropathy detection of type 2 diabetes using machine learning from TCM features: a cross-sectional study
Zhikui Tian, JiZhong Zhang, Yadong Fan, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access
Survey-Based Machine Learning Models for Early Detection of Diabetes
Eric Brown, Wei Lü
Lecture notes on data engineering and communications technologies (2025), pp. 109-122
Closed Access
Machine learning and artificial intelligence in type 2 diabetes prediction: a comprehensive 33-year bibliometric and literature analysis
Mahreen Kiran, Ying Xie, Nasreen Anjum, et al.
Frontiers in Digital Health (2025) Vol. 7
Open Access
Exploring the effectiveness of machine learning algorithms for early detection of Type-2 Diabetes Mellitus
S Gowthami, Raghavendra Reddy, Mohammed Riyaz Ahmed
Measurement Sensors (2023) Vol. 31, pp. 100983-100983
Open Access | Times Cited: 7
Predicting an Optimal Medication/Prescription Regimen for Patient Discordant Chronic Comorbidities Using Multi-Output Models
Ichchha Pradeep Sharma, Tam Nguyen, Shruti Ajay Singh, et al.
Information (2024) Vol. 15, Iss. 1, pp. 31-31
Open Access | Times Cited: 2
Artificial Intelligence Application for Anti-tumor Drug Synergy Prediction
Peng Zheng, Yanling Ding, Pengfei Zhang, et al.
Current Medicinal Chemistry (2024) Vol. 31, Iss. 40, pp. 6572-6585
Closed Access | Times Cited: 2
A Review on Trending Machine Learning Techniques for Type 2 Diabetes Mellitus Management
Panagiotis D. Petridis, Aleksandra S. Kristo, Angelos K. Sikalidis, et al.
Informatics (2024) Vol. 11, Iss. 4, pp. 70-70
Open Access | Times Cited: 2
Leveraging Shapley Additive Explanations for Feature Selection in Ensemble Models for Diabetes Prediction
Prasant Mohanty, Sharmila Anand John Francis, Rabindra K. Barik, et al.
Bioengineering (2024) Vol. 11, Iss. 12, pp. 1215-1215
Open Access | Times Cited: 2
Machine learning models for predicting the risk factor of carotid plaque in cardiovascular disease
Chengling Bin, Qin Li, Jing Tang, et al.
Frontiers in Cardiovascular Medicine (2023) Vol. 10
Open Access | Times Cited: 6
Exploring Predictive Factors for Heart Failure Progression in Hypertensive Patients Based on Medical diagnosis Data from the MIMIC-IV Database
Jin‐Myung Jung, Doyoon Kim, In-Kyung Hwang
(2024)
Open Access | Times Cited: 1
Integrated bagging-RF learning model for diabetes diagnosis in middle-aged and elderly population
Yuanwu Shi, Jiuye Sun
PeerJ Computer Science (2024) Vol. 10, pp. e2436-e2436
Open Access | Times Cited: 1
Developing and Preliminary Testing of a Machine Learning-Based Platform for Sales Forecasting Using a Gradient Boosting Approach
Antonio Panarese, Giuseppina Settanni, Valeria Vitti, et al.
Applied Sciences (2022) Vol. 12, Iss. 21, pp. 11054-11054
Open Access | Times Cited: 7
Environmental exposures in machine learning and data mining approaches to diabetes etiology: A scoping review
Sejal Mistry, Naomi O. Riches, Ramkiran Gouripeddi, et al.
Artificial Intelligence in Medicine (2022) Vol. 135, pp. 102461-102461
Open Access | Times Cited: 6
Predictive Machine Learning Techniques for Diabetes Detection: An Analytical Comparison
Archana Saini, Kalpna Guleria, Shagun Sharma
(2023)
Closed Access | Times Cited: 3
Type 2 Diabetes Mellitus: Early Detection using Machine Learning Classification
S Gowthami, Venkata Siva Reddy, Mohammed Riyaz Ahmed
International Journal of Advanced Computer Science and Applications (2023) Vol. 14, Iss. 6
Open Access | Times Cited: 3
A Comprehensive Analysis of Chinese, Japanese, Korean, US-PIMA Indian, and Trinidadian Screening Scores for Diabetes Risk Assessment and Prediction
Norma Latif Fitriyani, Muhammad Syafrudin, Siti Maghfirotul Ulyah, et al.
Mathematics (2022) Vol. 10, Iss. 21, pp. 4027-4027
Open Access | Times Cited: 5
Predicting Long-Term Type 2 Diabetes with Artificial Intelligence (AI): A Scoping Review
Salleh Sonko, Fathima Lamya, Mahmood Alzubaidi, et al.
Studies in health technology and informatics (2023)
Open Access | Times Cited: 2
The Use of Neural Networks for the Prediction of Type II Diabetes: A Comparison of Recent Advances and Perspectives
Mayra Tualombo, Luis D. Carlosama, Brandon A. J. Nieto, et al.
Smart innovation, systems and technologies (2024), pp. 37-47
Closed Access
A Comprehensive Approach for Using Hybrid Ensemble Methods for Diabetes Detection
Md Sakir Ahmed, Abhijit Bora
Advances in computer and electrical engineering book series (2024), pp. 1-15
Closed Access
Exploring Predictive Factors for Heart Failure Progression in Hypertensive Patients Based on Medical Diagnosis Data from the MIMIC-IV Database
Jin‐Myung Jung, Doyoon Kim, In-Kyung Hwang
Bioengineering (2024) Vol. 11, Iss. 6, pp. 531-531
Open Access
Machine learning-based predictive model for type 2 diabetes mellitus using genetic and clinical data
Helen Huang, Adan Khan, Charmy Parikh, et al.
Elsevier eBooks (2024), pp. 177-185
Closed Access
A Scoping Review of Supervised Machine Learning Techniques in Predicting the Prevalence of Type 2 Diabetes Mellitus

Medicine & health (2024) Vol. 19, Iss. 2, pp. 380-399
Open Access
Predicting Diabetes in Adults: Identifying Important Features in Unbalanced Data Over a 5-Year Cohort Study Using Machine Learning Algorithm
Maryam Talebi Moghaddam, Yunes Jahani, Zahra Arefzadeh, et al.
Research Square (Research Square) (2024)
Open Access
Factors associated with acquiring exercise habits through health guidance for metabolic syndrome among middle-aged Japanese workers: A machine learning approach
Jiawei Wan, Kyohsuke Wakaba, Takeshi Onoue, et al.
Preventive Medicine Reports (2024) Vol. 48, pp. 102915-102915
Open Access
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