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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:

Machine learning for prediction of diabetes risk in middle-aged Swedish people
Lara Lama, Oskar Wilhelmsson, Erik Norlander, et al.
Heliyon (2021) Vol. 7, Iss. 7, pp. e07419-e07419
Open Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

Machine learning and deep learning predictive models for type 2 diabetes: a systematic review
Luis Fregoso-Aparicio, Julieta Noguez, Luis Montesinos, et al.
Diabetology & Metabolic Syndrome (2021) Vol. 13, Iss. 1
Open Access | Times Cited: 113
Analysis of runoff generation driving factors based on hydrological model and interpretable machine learning method
Shuo Wang, Hui Peng, Qin Hu, et al.
Journal of Hydrology Regional Studies (2022) Vol. 42, pp. 101139-101139
Open Access | Times Cited: 97
Effective Handling of Missing Values in Datasets for Classification Using Machine Learning Methods
Ashokkumar Palanivinayagam, Robertas Damaševičius
Information (2023) Vol. 14, Iss. 2, pp. 92-92
Open Access | Times Cited: 43
An assessment of machine learning models and algorithms for early prediction and diagnosis of diabetes using health indicators
Victor Chang, Meghana Ashok Ganatra, Karl Hall, et al.
Healthcare Analytics (2022) Vol. 2, pp. 100118-100118
Closed Access | Times Cited: 62
Recent applications of machine learning and deep learning models in the prediction, diagnosis, and management of diabetes: a comprehensive review
Elaheh Afsaneh, Amin Sharifdini, Hadi Ghazzaghi, et al.
Diabetology & Metabolic Syndrome (2022) Vol. 14, Iss. 1
Open Access | Times Cited: 57
Machine Learning Models for Data-Driven Prediction of Diabetes by Lifestyle Type
Yifan Qin, Jinlong Wu, Xiao Wen, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 22, pp. 15027-15027
Open Access | Times Cited: 39
Prediction of type 2 diabetes mellitus onset using logistic regression-based scorecards
Yochai Edlitz, Eran Segal
eLife (2022) Vol. 11
Open Access | Times Cited: 24
Ensemble Streamflow Simulations in a Qinghai–Tibet Plateau Basin Using a Deep Learning Method with Remote Sensing Precipitation Data as Input
Jinqiang Wang, Zhanjie Li, Ling Zhou, et al.
Remote Sensing (2025) Vol. 17, Iss. 6, pp. 967-967
Open Access
Runoff Prediction in the Xijiang River Basin Based on Long Short-Term Memory with Variant Models and Its Interpretable Analysis
Qingqing Tian, Hang Gao, Yu Tian, et al.
Water (2023) Vol. 15, Iss. 18, pp. 3184-3184
Open Access | Times Cited: 10
Hydrologic interpretation of machine learning models for 10-daily streamflow simulation in climate sensitive upper Indus catchments
Haris Mushtaq, Taimoor Akhtar, Muhammad Zia ur Rahman Hashmi, et al.
Theoretical and Applied Climatology (2024) Vol. 155, Iss. 6, pp. 5525-5542
Open Access | Times Cited: 3
Development and Validation of Machine Learning Models for Identifying Prediabetes and Diabetes in Normoglycemia
Xiaodong Zhang, Weidong Yao, Dawei Wang, et al.
Diabetes/Metabolism Research and Reviews (2024) Vol. 40, Iss. 8
Open Access | Times Cited: 3
A novel deep learning model for early diabetes risk prediction using attention-enhanced deep belief networks with highly imbalanced data
Olusola Olabanjo, Ashiribo Senapon Wusu, Olufemi Olabanjo, et al.
International Journal of Information Technology (2025)
Open Access
Development of a 5-Year Risk Prediction Model for Transition From Prediabetes to Diabetes Using Machine Learning: Retrospective Cohort Study (Preprint)
Yongsheng Zhang, Hongyu Zhang, Da-Wei Wang, et al.
(2025)
Closed Access
Efficacy of a machine learning-based approach in predicting neurological prognosis of cervical spinal cord injury patients following urgent surgery within 24 h after injury
Tomoaki Shimizu, Kota Suda, Satoshi Maki, et al.
Journal of Clinical Neuroscience (2022) Vol. 107, pp. 150-156
Open Access | Times Cited: 15
A Comprehensive Survey on Diabetes Type-2 (T2D) Forecast Using Machine Learning
Satyanarayana Murthy Nimmagadda, Gunnam Suryanarayana, Gangu Bharath Kumar, et al.
Archives of Computational Methods in Engineering (2024) Vol. 31, Iss. 5, pp. 2905-2923
Closed Access | Times Cited: 3
Predicting the 2-Year Risk of Progression from Prediabetes to Diabetes Using Machine Learning among Chinese Elderly Adults
Qing Liu, Qing Zhou, Yifeng He, et al.
Journal of Personalized Medicine (2022) Vol. 12, Iss. 7, pp. 1055-1055
Open Access | Times Cited: 13
Extraction of human understandable insight from machine learning model for diabetes prediction
Tsehay Admassu Assegie, Thulasi Karpagam, Radha Mothukuri, et al.
Bulletin of Electrical Engineering and Informatics (2022) Vol. 11, Iss. 2, pp. 1126-1133
Open Access | Times Cited: 12
Investigating Gender and Age Variability in Diabetes Prediction: A Multi-Model Ensemble Learning Approach
Rishi Jain, Nitin Kumar Tripathi, Millie Pant, et al.
IEEE Access (2024) Vol. 12, pp. 71535-71554
Open 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
Research on wettability of nickel coating changes induced in the electrodeposition process
Bowen Yue, Guangming Zhu, Yanwei Wang, et al.
Journal of Electroanalytical Chemistry (2022) Vol. 910, pp. 116146-116146
Closed Access | Times Cited: 11
Efficient Automated Disease Diagnosis Using Machine Learning Models
Mehroush Banday, Sherin Zafar, Farheen Siddiqui
Smart innovation, systems and technologies (2022), pp. 230-236
Closed Access | Times Cited: 11
Assessing the Suitability of Boosting Machine-Learning Algorithms for Classifying Arsenic-Contaminated Waters: A Novel Model-Explainable Approach Using SHapley Additive exPlanations
Bemah Ibrahim, Anthony Ewusi, Isaac Ahenkorah
Water (2022) Vol. 14, Iss. 21, pp. 3509-3509
Open Access | Times Cited: 11
Hydrologic Interpretation of Machine Learning Models for 10-daily streamflow simulation in Climate sensitive Upper Indus Catchments
Haris Mushtaq, Taimoor Akhtar, Muhammad Zia-ur-Rahman Hashmi, et al.
(2022)
Open Access | Times Cited: 9
Characteristics of fatal occupational injuries in migrant workers in South Korea: A machine learning study
Ju-Yeun Lee, Woojoo Lee, Sung‐Il Cho
Heliyon (2023) Vol. 9, Iss. 9, pp. e20138-e20138
Open Access | Times Cited: 5
Extreme Gradient Boosting and Soft Voting Ensemble Classifier for Diabetes Prediction
Dayal Kumar Behera, Shreela Dash, Ajit Kumar Behera, et al.
(2021)
Closed Access | Times Cited: 12
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