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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:

Early detection of type 2 diabetes mellitus using machine learning-based prediction models
Leon Kopitar, Primož Kocbek, Leona Cilar, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 286

Showing 1-25 of 286 citing articles:

Diabetes mellitus, the fastest growing global public health concern: Early detection should be focused
Md. Jamal Hossain, Md. Al‐Mamun, Md. Rabiul Islam
Health Science Reports (2024) Vol. 7, Iss. 3
Open Access | Times Cited: 174
Machine learning based diabetes prediction and development of smart web application
Nazin Ahmed, Rayhan Ahammed, Md. Manowarul Islam, et al.
International Journal of Cognitive Computing in Engineering (2021) Vol. 2, pp. 229-241
Open Access | Times Cited: 107
Artificial Intelligence in Current Diabetes Management and Prediction
Akihiro Nomura, Masahiro Noguchi, Mitsuhiro Kometani, et al.
Current Diabetes Reports (2021) Vol. 21, Iss. 12
Open Access | Times Cited: 105
Predicting the Onset of Diabetes with Machine Learning Methods
Chun-Yang Chou, Ding‐Yang Hsu, Chun-Hung Chou
Journal of Personalized Medicine (2023) Vol. 13, Iss. 3, pp. 406-406
Open Access | Times Cited: 78
Hybrid stacked ensemble combined with genetic algorithms for diabetes prediction
Jafar Abdollahi, Babak Nouri-Moghaddam
Iran Journal of Computer Science (2022) Vol. 5, Iss. 3, pp. 205-220
Open Access | Times Cited: 76
An ensemble Machine Learning approach for predicting Type-II diabetes mellitus based on lifestyle indicators
Shahid Mohammad Ganie, Majid Bashir Malik
Healthcare Analytics (2022) Vol. 2, pp. 100092-100092
Open Access | Times Cited: 75
Gradient boosting decision tree becomes more reliable than logistic regression in predicting probability for diabetes with big data
Hiroe Seto, Asuka Oyama, Shuji Kitora, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 74
Causal machine learning for predicting treatment outcomes
Stefan Feuerriegel, Dennis Frauen, Valentyn Melnychuk, et al.
Nature Medicine (2024) Vol. 30, Iss. 4, pp. 958-968
Closed Access | Times Cited: 64
Interpretable machine-learning models for maximum displacements of RC beams under impact loading predictions
Dade Lai, Cristoforo Demartino, Yan Xiao
Engineering Structures (2023) Vol. 281, pp. 115723-115723
Closed Access | Times Cited: 46
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: 44
Advancements and Prospects of Machine Learning in Medical Diagnostics: Unveiling the Future of Diagnostic Precision
Sohaib Asif, Wenhui Yi, Saif Ur-Rehman, et al.
Archives of Computational Methods in Engineering (2024)
Closed Access | Times Cited: 25
Improving diabetes disease patients classification using stacking ensemble method with PIMA and local healthcare data
Md. Shamim Reza, Ruhul Amin, Rubia Yasmin, et al.
Heliyon (2024) Vol. 10, Iss. 2, pp. e24536-e24536
Open Access | Times Cited: 19
A multi-energy meta-model strategy for multi-step ahead energy load forecasting
Aristeidis Mystakidis, Evangelia Ntozi, Paraskevas Koukaras, et al.
Electrical Engineering (2025)
Open Access | Times Cited: 2
A patient network-based machine learning model for disease prediction: The case of type 2 diabetes mellitus
Haohui Lu, Shahadat Uddin, Farshid Hajati, et al.
Applied Intelligence (2021) Vol. 52, Iss. 3, pp. 2411-2422
Closed Access | Times Cited: 98
Real-time rainfall-runoff prediction using light gradient boosting machine coupled with singular spectrum analysis
Zhongjie Cui, Qing Xiaoxia, Hongxiang Chai, et al.
Journal of Hydrology (2021) Vol. 603, pp. 127124-127124
Closed Access | Times Cited: 69
Data-Driven Machine-Learning Methods for Diabetes Risk Prediction
Ηλίας Δρίτσας, Μαρία Τρίγκα
Sensors (2022) Vol. 22, Iss. 14, pp. 5304-5304
Open Access | Times Cited: 67
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: 58
Machine learning for diabetes clinical decision support: a review
Ashwini Tuppad, Shantala Devi Patil
Advances in Computational Intelligence (2022) Vol. 2, Iss. 2
Open Access | Times Cited: 49
TransformEHR: transformer-based encoder-decoder generative model to enhance prediction of disease outcomes using electronic health records
Zhichao Yang, Avijit Mitra, Weisong Liu, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 39
Diabetes detection based on machine learning and deep learning approaches
Boon Feng Wee, Saaveethya Sivakumar, King Hann Lim, et al.
Multimedia Tools and Applications (2023) Vol. 83, Iss. 8, pp. 24153-24185
Open Access | Times Cited: 38
Unmanned aerial vehicle (UAV) imaging and machine learning applications for plant phenotyping
Fitsum T. Teshome, Haimanote K. Bayabil, Gerrit Hoogenboom, et al.
Computers and Electronics in Agriculture (2023) Vol. 212, pp. 108064-108064
Open Access | Times Cited: 36
HealthEdge: A Machine Learning-Based Smart Healthcare Framework for Prediction of Type 2 Diabetes in an Integrated IoT, Edge, and Cloud Computing System
Alain Hennebelle, Huned Materwala, Leila Ismail
Procedia Computer Science (2023) Vol. 220, pp. 331-338
Open Access | Times Cited: 34
Comprehensive machine and deep learning analysis of sensor-based human activity recognition
Hossam Magdy Balaha, Asmaa El-Sayed Hassan
Neural Computing and Applications (2023) Vol. 35, Iss. 17, pp. 12793-12831
Closed Access | Times Cited: 31
Secure and privacy-preserving automated machine learning operations into end-to-end integrated IoT-edge-artificial intelligence-blockchain monitoring system for diabetes mellitus prediction
Alain Hennebelle, Leila Ismail, Huned Materwala, et al.
Computational and Structural Biotechnology Journal (2023) Vol. 23, pp. 212-233
Open Access | Times Cited: 29
An Ensemble of Light Gradient Boosting Machine and Adaptive Boosting for Prediction of Type-2 Diabetes
M. Jishnu Sai, Pratiksha Chettri, Ranjit Panigrahi, et al.
International Journal of Computational Intelligence Systems (2023) Vol. 16, Iss. 1
Open Access | Times Cited: 26
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