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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:

Cardiovascular complications in a diabetes prediction model using machine learning: a systematic review
Ooi Ting Kee, Harmiza Harun, Norlaila Mustafa, et al.
Cardiovascular Diabetology (2023) Vol. 22, Iss. 1
Open Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
Gary S. Collins, Karel G.M. Moons, Paula Dhiman, et al.
BMJ (2024), pp. e078378-e078378
Open Access | Times Cited: 263
Exploring the Intersection of Artificial Intelligence and Clinical Healthcare: A Multidisciplinary Review
Celina Silvia Stafie, Irina-Georgeta Șufaru, Cristina Mihaela Ghiciuc, et al.
Diagnostics (2023) Vol. 13, Iss. 12, pp. 1995-1995
Open Access | Times Cited: 48
Machine learning in precision diabetes care and cardiovascular risk prediction
Evangelos K. Oikonomou, Rohan Khera
Cardiovascular Diabetology (2023) Vol. 22, Iss. 1
Open Access | Times Cited: 47
THE PREDICTION OF HEART DISEASE USING MACHINE LEARNING ALGORITHMS
Snwr J. Mohammed, Noor Tayfor
Science Journal of University of Zakho (2024) Vol. 12, Iss. 3, pp. 285-293
Open Access | Times Cited: 17
Artificial intelligence, nutrition, and ethical issues: A mini-review
Paraskevi Detopoulou, Gavriela Voulgaridou, Panagiotis Moschos, et al.
Clinical Nutrition Open Science (2023) Vol. 50, pp. 46-56
Closed Access | Times Cited: 21
Predicting coronary heart disease in Chinese diabetics using machine learning
Cai-Yi Ma, Yamei Luo, Tianyu Zhang, et al.
Computers in Biology and Medicine (2024) Vol. 169, pp. 107952-107952
Closed Access | Times Cited: 14
Prediction model for cardiovascular disease in patients with diabetes using machine learning derived and validated in two independent Korean cohorts
Hyunji Sang, Hojae Lee, Myeongcheol Lee, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
AI hybrid survival assessment for advanced heart failure patients with renal dysfunction
Ge Zhang, Zeyu Wang, Zhuang Tong, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 4
Overcoming Missing Data: Accurately Predicting Cardiovascular Risk in Type 2 Diabetes, A Systematic Review
Wenhui Ren, K FAN, Zheng Liu, et al.
Journal of Diabetes (2025) Vol. 17, Iss. 1
Open Access
Unveiling diabetes onset: Optimized XGBoost with Bayesian optimization for enhanced prediction
Muhammad Khurshid, Sadaf Manzoor, Touseef Sadiq, et al.
PLoS ONE (2025) Vol. 20, Iss. 1, pp. e0310218-e0310218
Open Access
PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods
Karel G.M. Moons, Johanna AAG Damen, T. K. Kaul, et al.
BMJ (2025), pp. e082505-e082505
Closed Access
Leveraging Regression Analysis to Predict Overlapping Symptoms of Cardiovascular Diseases
Sara Ghorashi, Khunsa Rehman, Anam Riaz, et al.
IEEE Access (2023) Vol. 11, pp. 60254-60266
Open Access | Times Cited: 12
Machine learning in the prediction and detection of new-onset atrial fibrillation in ICU: a systematic review
K. Glaser, Luca Marino, János Domonkos Stubnya, et al.
Journal of Anesthesia (2024) Vol. 38, Iss. 3, pp. 301-308
Open Access | Times Cited: 3
Machine learning reveals serum myristic acid, palmitic acid and heptanoylcarnitine as biomarkers of coronary artery disease risk in patients with type 2 diabetes mellitus
Ting Hu, Wen Zhang, Feifei Han, et al.
Clinica Chimica Acta (2024) Vol. 556, pp. 117852-117852
Closed Access | Times Cited: 1
A multimodal approach using fundus images and text meta-data in a machine learning classifier with embeddings to predict years with self-reported diabetes – An exploratory analysis
Rodrigo M. Carrillo‐Larco, Gusseppe Bravo-Rocca, Manuel Castillo-Cara, et al.
Primary care diabetes (2024) Vol. 18, Iss. 3, pp. 327-332
Closed Access | Times Cited: 1
Predicting Diabetes with Machine Learning Analysis of Income and Health Factors Detection
Fariba Jafari Horestani, M. Mehdi Owrang O
Software Engineering (2024), pp. 137-154
Open Access | Times Cited: 1
A comparative histopathological study of pancreas, intestine, and liver of experimentally induced diabetes in rats
Meaad A. Ali, Nashaat G. Mustafa
˜Al-œmağallaẗ al-ʻirāqiyyaẗ li-l-ʻulūm al-bayṭariyyaẗ/Iraqi journal of veterinary sciences (2023) Vol. 37, Iss. 4, pp. 971-978
Open Access | Times Cited: 3
Progress in Cardiac Magnetic Resonance Feature Tracking for Evaluating Myocardial Strain in Type-2 Diabetes Mellitus
Liting Shen, Rui Shi, Zhi‐gang Yang, et al.
Current Diabetes Reviews (2024) Vol. 20, Iss. 8
Open Access
Interplay of cardiovascular health and diabetes: Insights into weight management and risk reduction
Chih‐Yao Hsu, Hung‐Yuan Li
Journal of Diabetes Investigation (2024) Vol. 15, Iss. 6, pp. 707-710
Open Access
Integrated Embedded system for detecting diabetes mellitus using various machine learning techniques
Rishita Konda, Anuraag Ramineni, J. Jayashree, et al.
EAI Endorsed Transactions on Pervasive Health and Technology (2024) Vol. 10
Open Access
An Effective Framework for Early Detection and Classification of Cardiovascular Disease (CVD) Using Machine Learning Techniques
Shailendra Chaurasia, Megha Kamble
Lecture notes in networks and systems (2024), pp. 21-44
Closed Access
Machine learning-based model to predict severe acute kidney injury after total aortic arch replacement for acute type A aortic dissection
Xiaolong Liu, Miaoxian Fang, Kai Wang, et al.
Heliyon (2024) Vol. 10, Iss. 13, pp. e34171-e34171
Open Access
A Comprehensive Survey on Diabetes Forecasting Using ML
Dev Mittal, Sanjeev Sofat, Amandeep Kaur
(2024), pp. 1-5
Closed Access
PEFNN: Parallel Evolving Fuzzy Neural Network for Sepsis Identification in Patients
Paulo Vitor de Campos Souza, Mauro Dragoni
2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (2024), pp. 1-9
Closed Access
Predicting the risks for stroke, cardiovascular disease, and peripheral vascular disease among people with type 2 diabetes with artificial intelligence models: a systematic review and meta-analysis
Aqsha Azhary Nur, Sydney Tjandra, Defin Allevia Yumnanisha, et al.
(2024)
Open Access
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