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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 Models for Inpatient Glucose Prediction
Andrew D. Zale, Nestoras Mathioudakis
Current Diabetes Reports (2022) Vol. 22, Iss. 8, pp. 353-364
Open Access | Times Cited: 23

Showing 23 citing articles:

16. Diabetes Care in the Hospital: Standards of Care in Diabetes—2025
Nuha A. ElSayed, Rozalina G. McCoy, Grazia Aleppo, et al.
Diabetes Care (2024) Vol. 48, Iss. Supplement_1, pp. S321-S334
Closed Access | Times Cited: 16
Data-based modeling for hypoglycemia prediction: Importance, trends, and implications for clinical practice
Liyin Zhang, Lin Yang, Zhiguang Zhou
Frontiers in Public Health (2023) Vol. 11
Open Access | Times Cited: 23
Artificial Intelligence for Predicting and Diagnosing Complications of Diabetes
Jingtong Huang, Andrea M. Yeung, David G. Armstrong, et al.
Journal of Diabetes Science and Technology (2022) Vol. 17, Iss. 1, pp. 224-238
Open Access | Times Cited: 33
A Meaningful Machine Learning Model for Predicting Amputation Rate of Patients with Diabetic Foot
Zixuan Liu, Siyang Han, Lei Gao, et al.
Research Square (Research Square) (2025)
Closed Access
Inpatient Hypoglycemic Rate Reduction Through the Implementation of Prescriber Targeted Decision Support Tools
Jessica Odom, Rebecca F. Goldstein
Current Diabetes Reports (2025) Vol. 25, Iss. 1
Closed Access
GARNN: An interpretable graph attentive recurrent neural network for predicting blood glucose levels via multivariate time series
Chengzhe Piao, Taiyu Zhu, Stephanie Baldeweg, et al.
Neural Networks (2025) Vol. 185, pp. 107229-107229
Open Access
Glu-Ensemble: An ensemble deep learning framework for blood glucose forecasting in type 2 diabetes patients
Yechan Han, Dae-Yeon Kim, Jiyoung Woo, et al.
Heliyon (2024) Vol. 10, Iss. 8, pp. e29030-e29030
Open Access | Times Cited: 3
Inpatient diabetes management
Andrew P. Demidowich, Camille Stanback, Mihail Zilbermint
Annals of the New York Academy of Sciences (2024) Vol. 1538, Iss. 1, pp. 5-20
Closed Access | Times Cited: 3
Hierarchical federated learning for health trend prediction and anomaly detection using pharmacy data: from zone to national scale
Goran Saman Nariman, Hozan K. Hamarashid
International Journal of Data Science and Analytics (2025)
Closed Access
Machine learning and artificial intelligence for the diagnosis of infectious diseases in immunocompromised patients
Nam K. Tran, Cileah M. Kretsch, Clayton LaValley, et al.
Current Opinion in Infectious Diseases (2023)
Closed Access | Times Cited: 9
Point of care blood glucose devices in the hospital setting
Nam K. Tran, Clayton LaValley, Berit Bagley, et al.
Critical Reviews in Clinical Laboratory Sciences (2023) Vol. 60, Iss. 4, pp. 290-299
Closed Access | Times Cited: 7
Application of machine learning in affordable and accessible insulin management for type 1 and 2 diabetes: A comprehensive review
Maryam Eghbali‐Zarch, Sara Masoud
Artificial Intelligence in Medicine (2024) Vol. 151, pp. 102868-102868
Closed Access | Times Cited: 2
A Clinician’s Guide to Understanding Bias in Critical Clinical Prediction Models
João Matos, Jack Gallifant, Anand Chowdhury, et al.
Critical Care Clinics (2024) Vol. 40, Iss. 4, pp. 827-857
Closed Access | Times Cited: 2
On the Selectivity of Planar Microwave Glucose Sensors with Multicomponent Solutions
Carlos G. Juan, E. Bronchalo, Benjamin Potelon, et al.
Electronics (2022) Vol. 12, Iss. 1, pp. 191-191
Open Access | Times Cited: 11
A Meaningful Machine Learning Model for Predicting Amputation Rate of Patients with Diabetic Foot Ulcer
Zixuan Liu, Siyang Han, Lei Gao, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 1
Riemannian manifold-based geometric clustering of continuous glucose monitoring to improve personalized diabetes management
J. Song, J. McNeany, Yifei Wang, et al.
Computers in Biology and Medicine (2024) Vol. 183, pp. 109255-109255
Closed Access | Times Cited: 1
Heterogeneous temporal representation for diabetic blood glucose prediction
Yaohui Huang, Zhikai Ni, Zhenkun Lu, et al.
Frontiers in Physiology (2023) Vol. 14
Open Access | Times Cited: 3
Smart System for Predicting the Diabetes using Machine Learning Techniques
Saravanan Alagarsamy, P. Muthuvel, K. V. Sudheer Kumar, et al.
(2023)
Closed Access | Times Cited: 2
Development and Validation of Inpatient Hypoglycemia Models Centered Around the Insulin Ordering Process
Aileen P Wright, Peter J. Embí, Scott D. Nelson, et al.
Journal of Diabetes Science and Technology (2022) Vol. 18, Iss. 2, pp. 423-429
Open Access | Times Cited: 4
Prediction of Next Glucose Measurement in Hospitalized Patients by Comparing Various Regression Methods: Retrospective Cohort Study
Andrew D. Zale, Mohammed S. Abusamaan, John McGready, et al.
JMIR Formative Research (2022) Vol. 7, pp. e41577-e41577
Open Access | Times Cited: 3
Introduction to Artificial Intelligence in Diabetes
Andrew D. Zale, Mohammed S. Abusamaan, Nestoras Mathioudakis
Elsevier eBooks (2024), pp. 249-261
Closed Access
Predicting hypoglycemia in ICU patients: a machine learning approach
Reema Karasneh, Sayer Al‐Azzam, Karem H. Alzoubi, et al.
Expert Review of Endocrinology & Metabolism (2024), pp. 1-8
Closed Access
Machine Learning Based in Quantum Mechanics and Theorem of Bayes
Huber Nieto–Chaupis
2021 International Conference on Electrical, Computer and Energy Technologies (ICECET) (2024), pp. 1-6
Closed Access
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