Type 1 Diabetes Hypoglycemia Prediction Algorithms: Systematic Review

Journals

1. D'Antoni F, Petrosino L, Marchetti A, Bacco L, Pieralice S, Vollero L, Pozzilli P, Piemonte V, Merone M. Layered Meta-Learning Algorithm for Predicting Adverse Events in Type 1 Diabetes. IEEE Access 2023;11:9074 View
2. Lehmann V, Zueger T, Maritsch M, Kraus M, Albrecht C, Bérubé C, Feuerriegel S, Wortmann F, Kowatsch T, Styger N, Lagger S, Laimer M, Fleisch E, Stettler C. Machine learning for non‐invasive sensing of hypoglycaemia while driving in people with diabetes. Diabetes, Obesity and Metabolism 2023;25(6):1668 View
3. Detopoulou P, Voulgaridou G, Moschos P, Levidi D, Anastasiou T, Dedes V, Diplari E, Fourfouri N, Giaginis C, Panoutsopoulos G, Papadopoulou S. Artificial intelligence, nutrition, and ethical issues: A mini-review. Clinical Nutrition Open Science 2023;50:46 View
4. Chen E, Prakash S, Janapa Reddi V, Kim D, Rajpurkar P. A framework for integrating artificial intelligence for clinical care with continuous therapeutic monitoring. Nature Biomedical Engineering 2023;9(4):445 View
5. Litvinova O, Eitenberger M, Bilir A, Yeung A, Parvanov E, MohanaSundaram A, Horbańczuk J, Atanasov A, Willschke H. Patent analysis of digital sensors for continuous glucose monitoring. Frontiers in Public Health 2023;11 View
6. Zrubka Z, Kertész G, Gulácsi L, Czere J, Hölgyesi Á, Nezhad H, Mosavi A, Kovács L, Butte A, Péntek M. The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review. Journal of Medical Internet Research 2024;26:e47430 View
7. Marx A, Di Stefano F, Leutheuser H, Chin-Cheong K, Pfister M, Burckhardt M, Bachmann S, Vogt J. Blood glucose forecasting from temporal and static information in children with T1D. Frontiers in Pediatrics 2023;11 View
8. Freeman N, Muthukkumar R, Weinstock R, Wickerhauser M, Kahkoska A. Use of machine learning to identify characteristics associated with severe hypoglycemia in older adults with type 1 diabetes: a post-hoc analysis of a case–control study. BMJ Open Diabetes Research & Care 2024;12(1):e003748 View
9. Butunoi B, Stolojescu-Crisan C, Negru V. Short-term glucose prediction in Type 1 Diabetes. Procedia Computer Science 2024;238:41 View
10. Kladov D, Berikov V, Semenova J, Klimontov V. Machine Learning Algorithms Based on Time Series Pre-Clustering for Nocturnal Glucose Prediction in People with Type 1 Diabetes. Diagnostics 2024;14(21):2427 View
11. Hussain S, Bresnahan M, Zhuang J. The bias algorithm: how AI in healthcare exacerbates ethnic and racial disparities – a scoping review. Ethnicity & Health 2025;30(2):197 View
12. Ayers A, Ho C, Kerr D, Cichosz S, Mathioudakis N, Wang M, Najafi B, Moon S, Pandey A, Klonoff D. Artificial Intelligence to Diagnose Complications of Diabetes. Journal of Diabetes Science and Technology 2025;19(1):246 View
13. Piersanti A, Morettini M, Cristino S, Giudice L, Burattini L, Mosconi G, Göbl C, Mambelli E, Tura A. Assessing hypoglycemia risk during hemodialysis using an explainable machine learning approach based on continuous glucose monitoring metrics. Biomedical Signal Processing and Control 2025;102:107319 View
14. Lara-Abelenda F, Chushig-Muzo D, Wägner A, Tayefi M, Soguero-Ruiz C. Interpretable and multimodal fusion methodology to predict severe hypoglycemia in adults with type 1 diabetes. Engineering Applications of Artificial Intelligence 2025;144:110142 View
15. Katsarou D, Georga E, Christou M, Christou P, Tigas S, Papaloukas C, Fotiadis D. Optimizing hypoglycaemia prediction in type 1 diabetes with Ensemble Machine Learning modeling. BMC Medical Informatics and Decision Making 2025;25(1) View
16. Yadav A, Yadav K. Transforming healthcare and fitness with AI powered next-generation smart clothing. Discover Electrochemistry 2025;2(1) View
17. Xia Y, Zhang M, Yao Y, Cai T, Mo H, Shen J, Lou J. Epidemiology and reporting characteristics of systematic reviews of clinical prediction models: a scoping review. Journal of Clinical Epidemiology 2025;182:111763 View
18. Marchetti A, Sasso D, D’Antoni F, Morandin F, Parton M, Matarrese M, Merone M. Deep reinforcement learning for Type 1 Diabetes: Dual PPO controller for personalized insulin management. Computers in Biology and Medicine 2025;191:110147 View

Books/Policy Documents

1. Katsarou D, Georga E, Christou M, Tigas S, Papaloukas C, Fotiadis D. Pervasive Computing Technologies for Healthcare. View
2. Choudhury A, Sarma K. Investigations in Pattern Recognition and Computer Vision for Industry 4.0. View
3. Onwuchekwa J, Weber C, Maleshkova M. The Semantic Web: ESWC 2024 Satellite Events. View
4. Goel J, Gupta S, Vijarania M, Vijarania P. AI-Driven Personalized Healthcare Solutions. View

Conference Proceedings

1. Goyal J, Sharma N, Kumar A, Anand A, Prabha C. 2023 IEEE 2nd International Conference on Industrial Electronics: Developments & Applications (ICIDeA). Classifying Diabetes Using Artificially Intelligent Techniques: A Comparative Analysis View
2. D’Antoni F, Bertazzoni M, Vollero L, Merone M. 2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC). Identification of the Optimal Meal Detection Strategy for Adults, Adolescents, and Children with Type 1 Diabetes: an in Silico Validation View
3. Joshi A, Merickel J, Desouza C, Rizzo M, Gunaratne P, Sharma A. 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC). Investigating Speed Deviation Patterns During Glucose Episodes: A Quantile Regression Approach View
4. Katsarou D, Georga E, Sakaloglou P, Christou M, Georgiou I, Tigas S, Papaloukas C, Fotiadis D. 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Glucose Prediction Using Population-based Models and Genetic Data in Type 1 Diabetes Patients View