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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:

Basal Glucose Control in Type 1 Diabetes Using Deep Reinforcement Learning: An In Silico Validation
Taiyu Zhu, Kezhi Li, Pau Herrero, et al.
IEEE Journal of Biomedical and Health Informatics (2020) Vol. 25, Iss. 4, pp. 1223-1232
Open Access | Times Cited: 68

Showing 1-25 of 68 citing articles:

Deep Learning for Diabetes: A Systematic Review
Taiyu Zhu, Kezhi Li, Pau Herrero, et al.
IEEE Journal of Biomedical and Health Informatics (2020) Vol. 25, Iss. 7, pp. 2744-2757
Open Access | Times Cited: 168
Machine Learning Techniques for Hypoglycemia Prediction: Trends and Challenges
Omer Mujahid, Iván Contreras, Josep Vehı́
Sensors (2021) Vol. 21, Iss. 2, pp. 546-546
Open Access | Times Cited: 72
IoMT-Enabled Real-Time Blood Glucose Prediction With Deep Learning and Edge Computing
Taiyu Zhu, Lei Kuang, John Daniels, et al.
IEEE Internet of Things Journal (2022) Vol. 10, Iss. 5, pp. 3706-3719
Closed Access | Times Cited: 65
Enhancing self-management in type 1 diabetes with wearables and deep learning
Taiyu Zhu, Chukwuma Uduku, Kezhi Li, et al.
npj Digital Medicine (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 53
Personalized Blood Glucose Prediction for Type 1 Diabetes Using Evidential Deep Learning and Meta-Learning
Taiyu Zhu, Kezhi Li, Pau Herrero, et al.
IEEE Transactions on Biomedical Engineering (2022) Vol. 70, Iss. 1, pp. 193-204
Open Access | Times Cited: 50
Artificial Intelligence and Machine Learning for Improving Glycemic Control in Diabetes: Best Practices, Pitfalls, and Opportunities
Peter G. Jacobs, Pau Herrero, Andrea Facchinetti, et al.
IEEE Reviews in Biomedical Engineering (2023) Vol. 17, pp. 19-41
Open Access | Times Cited: 34
Offline reinforcement learning for safer blood glucose control in people with type 1 diabetes
Harry Emerson, Matthew Guy, Ryan McConville
Journal of Biomedical Informatics (2023) Vol. 142, pp. 104376-104376
Open Access | Times Cited: 32
An Insulin Bolus Advisor for Type 1 Diabetes Using Deep Reinforcement Learning
Taiyu Zhu, Kezhi Li, Lei Kuang, et al.
Sensors (2020) Vol. 20, Iss. 18, pp. 5058-5058
Open Access | Times Cited: 58
A comprehensive review of models and nonlinear control strategies for blood glucose regulation in artificial pancreas
Iqra Shafeeq Mughal, Luca Patanè, Riccardo Caponetto
Annual Reviews in Control (2024) Vol. 57, pp. 100937-100937
Open Access | Times Cited: 7
Optimized blockchain-based healthcare framework empowered by mixed multi-agent reinforcement learning
Abeer Z. Al-Marridi, Amr Mohamed, Aiman Erbad
Journal of Network and Computer Applications (2024) Vol. 224, pp. 103834-103834
Closed Access | Times Cited: 6
Electronic health records based reinforcement learning for treatment optimizing
Tianhao Li, Zhishun Wang, Wei Lü, et al.
Information Systems (2021) Vol. 104, pp. 101878-101878
Closed Access | Times Cited: 40
Blood Glucose Prediction in Type 1 Diabetes Using Deep Learning on the Edge
Taiyu Zhu, Lei Kuang, Kezhi Li, et al.
2022 IEEE International Symposium on Circuits and Systems (ISCAS) (2021)
Open Access | Times Cited: 35
Reinforcement Learning for Intelligent Healthcare Systems: A Review of Challenges, Applications, and Open Research Issues
Alaa Awad Abdellatif, Naram Mhaisen, Amr Mohamed, et al.
IEEE Internet of Things Journal (2023) Vol. 10, Iss. 24, pp. 21982-22007
Open Access | Times Cited: 15
Reinforcement Learning Models and Algorithms for Diabetes Management
Kok‐Lim Alvin Yau, Yung-Wey Chong, Xiumei Fan, et al.
IEEE Access (2023) Vol. 11, pp. 28391-28415
Open Access | Times Cited: 13
GluGAN: Generating Personalized Glucose Time Series Using Generative Adversarial Networks
Taiyu Zhu, Kezhi Li, Pau Herrero, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 27, Iss. 10, pp. 5122-5133
Open Access | Times Cited: 13
A safe-enhanced fully closed-loop artificial pancreas controller based on deep reinforcement learning
Yan Feng Zhao, Jun Kit Chaw, Mei Choo Ang, et al.
PLoS ONE (2025) Vol. 20, Iss. 1, pp. e0317662-e0317662
Open Access
Generalized reinforcement learning control algorithm for fully automated insulin delivery system
Vega Pradana Rachim, J. Yoo, Jaeyeon Lee, et al.
Expert Systems with Applications (2025), pp. 126909-126909
Closed Access
Artificial Pancreas Control Strategies Used for Type 1 Diabetes Control and Treatment: A Comprehensive Analysis
Sohaib Mehmood, Imran Ahmad, Hadeeqa Arif, et al.
Applied System Innovation (2020) Vol. 3, Iss. 3, pp. 31-31
Open Access | Times Cited: 35
Deep reinforcement learning-based control of chemo-drug dose in cancer treatment
Hoda Mashayekhi, Mostafa Nazari, Fatemeh Jafarinejad, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 243, pp. 107884-107884
Closed Access | Times Cited: 12
A Personalized and Adaptive Insulin Bolus Calculator Based on Double Deep Q- Learning to Improve Type 1 Diabetes Management
Giulia Noaro, Taiyu Zhu, Giacomo Cappon, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 27, Iss. 5, pp. 2536-2544
Open Access | Times Cited: 11
Chronic Care in a Life Transition: Challenges and Opportunities for Artificial Intelligence to Support Young Adults With Type 1 Diabetes Moving to University
Sam James, Miranda Armstrong, Zahraa S. Abdallah, et al.
(2023), pp. 1-16
Open Access | Times Cited: 11
A Blood Glucose Control Framework Based on Reinforcement Learning With Safety and Interpretability: In Silico Validation
Min Hyuk Lim, Woo Hyung Lee, Byoungjun Jeon, et al.
IEEE Access (2021) Vol. 9, pp. 105756-105775
Open Access | Times Cited: 20
Intelligent Control with Artificial Neural Networks for Automated Insulin Delivery Systems
João Lucas Correia Barbosa de Farias, Wallace Moreira Bessa
Bioengineering (2022) Vol. 9, Iss. 11, pp. 664-664
Open Access | Times Cited: 14
Deep Offline Reinforcement Learning for Real-world Treatment Optimization Applications
Mila Nambiar, Supriyo Ghosh, Priscilla Ong, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2023), pp. 4673-4684
Open Access | Times Cited: 8
Long-term use of the hybrid artificial pancreas by adjusting carbohydrate ratios and programmed basal rate: A reinforcement learning approach
Adnan Jafar, Anas El Fathi, Ahmad Haidar
Computer Methods and Programs in Biomedicine (2021) Vol. 200, pp. 105936-105936
Closed Access | Times Cited: 19
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