A review of personalized blood glucose prediction strategies for T1DM patients

Oviedo, Silvia, Vehí, Josep, Calm, Remei, Armengol, Joaquim·2017·International Journal for Numerical Methods in Biomedical Engineering
DOI 10.1002/cnm.2833

Cited by (282)

Items 101–200 of 282

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  5. Prediction of Blood Glucose Level Using Nonlinear System Identification Approach
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  7. Multi-step ahead predictive model for blood glucose concentrations of type-1 diabetic patients
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  9. Using Grammatical Evolution to Generate Short-term Blood Glucose Prediction Models.
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  10. Reducing High-Risk Glucose Forecasting Errors by Evolving Interpretable Models for Type 1 Diabetes
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  11. Enhancing glucose level prediction of ICU patients through hierarchical modeling of irregular time-series
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  12. Identifiability of Control-Oriented Glucose-Insulin Linear Models: Review and Analysis
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  13. Adaptive basal insulin recommender system based on Kalman filter for type 1 diabetes
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  14. A fundamental control performance limit for a class of positive nonlinear systems
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  15. Digital Solutions to Diagnose and Manage Postbariatric Hypoglycemia
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  16. Platform for precise, personalised glucose forecasting through continuous glucose and physical activity monitoring and deep learning
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  17. Enhancing Personalized Blood Glucose Prediction: Deep Learning Insights From Ablation Study on Wearable Sensor Data
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  18. Hypoglycemia Prevention via Personalized Glucose-Insulin Models Identified in Free-Living Conditions
    Chiara Toffanin, Eleonora M. Aiello, Claudio Cobelli, Lalo Magni · 2019 · Journal of Diabetes Science and Technology
  19. Neural Physiological Model: A Simple Module for Blood Glucose Prediction
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  20. GlucoMine
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  21. Personalized blood glucose prediction in type 1 diabetes using meta-learning with bidirectional long short term memory-transformer hybrid model
    Kihoon Moon, Jaehong Kim, Seohyun Yoo, Jaehyuk Cho · 2025 · Scientific Reports
  22. A New Glycemic closed-loop control based on Dyna-Q for Type-1-Diabetes
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  23. Multiple order model migration and optimal model selection for online glucose prediction in Type 1 diabetes
    Hong Zhao, Chunhui Zhao, Chengxia Yu, Eyal Dassau · 2017 · AIChE Journal
  24. Feedback and feedforward control in the context of model predictive control with application to the management of type 1 diabetes mellitus
    Graham C. Goodwin, Maria Marta Seron · 2019 · Control Engineering Practice
  25. Prediction-Coherent LSTM-Based Recurrent Neural Network for Safer Glucose Predictions in Diabetic People
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  27. Blood Glucose Prediction Using RNN, LSTM, and GRU: A Comparative Study
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  29. Study of Short-Term Personalized Glucose Predictive Models on Type-1 Diabetic Children
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  30. Predicting Blood Glucose Levels with Organic Neuromorphic Micro‐Networks
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  31. A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism
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  33. Data Driven Patient-Specialized Neural Networks for Blood Glucose Prediction
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    Virginie Felizardo, Diogo Machado, Nuno M. García, Nuno Gonçalo Coelho Costa Pombo, Pedro Brandão · 2021 · IEEE Access
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  39. Systematic Review on Deep Learning Algorithms for Blood Glucose Forecasting in Type 1 Diabetes
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  44. Forecasting glycaemia for type 1 diabetes mellitus patients by means of IoMT devices
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  47. Blood Glucose Prediction from Nutrition Analytics in Type 1 Diabetes: A Review
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  48. Multivariate Glucose Forecasting Using Deep Multihead Attention Layers Inside Neural Basis Expansion Networks
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  51. A mapping study on blood glucose recommender system for patients with gestational diabetes mellitus
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  54. A Critique of Observers Used in the Context of Feedback Control
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  55. Forecasting postbariatric hypoglycaemia in patients after Roux‐en‐Y gastric bypass using model‐based algorithms fed by continuous glucose monitoring data: A proof‐of‐concept study
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  56. Artificial Intelligence and Machine Learning for Diabetes Decision Support
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  57. Assessment of Seasonal Stochastic Local Models for Glucose Prediction without Meal Size Information under Free-Living Conditions
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  58. Jointly Predicting Postprandial Hypoglycemia and Hyperglycemia Using Continuous Glucose Monitoring Data in Type 1 Diabetes
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  59. Multiscale modeling of solid starch-based foods digestion in the intestinal tract for dietary property-based glycemic prediction
    Yifan Qin, Jie Xiao, Aibing Yu, Xiao Dong Chen · 2024 · Food Research International
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  61. A predictive model incorporating the change detection and Winsorization methods for alerting hypoglycemia and hyperglycemia
    Lei Li, Xiaolei Xie, Jun Hu Yang · 2021 · Medical & Biological Engineering & Computing
  62. A Comparison of Machine Learning Algorithms in Blood Glucose Prediction for People with Type 1 Diabetes
    Yiyang Wang · 2021 · International Symposium on Artificial Intelligence for Medicine Sciences (ISAIMS)
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    Sofia Goel, Sudhansh Sharma, RC Tripathi · 2021 · International Conference on System Modeling & Advancement in Research Trends (SMART)
  64. Enhancing Blood Glucose Prediction with Meal Absorption and Physical Exercise Information
    Chengyuan Liu, J. Vehí, N. Oliver, P. Georgiou, P. Herrero · 2018 · arXiv.org
  65. A Longitudinal Multimodal Dataset of Type 1 Diabetes
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  66. Shortcomings in the Evaluation of Blood Glucose Forecasting
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  68. Identification of individuals with diabetes who are eligible for continuous glucose monitoring forecasting
    Simon Lebech Cichosz, Ole Kristian Hejlesen, Morten Hasselstrøm Jensen · 2024 · Diabetes & Metabolic Syndrome Clinical Research & Reviews
  69. Optimizing postprandial glucose prediction through integration of diet and exercise: Leveraging transfer learning with imbalanced patient data
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  70. Blood Glucose Concentration Prediction Based on Canonical Correlation Analysis
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  71. Examining Sensor Agreement in Neural Network Blood Glucose Prediction
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  73. Integration of clinical criteria into the training of deep models: Application to glucose prediction for diabetic people
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  74. The development of a glucose prediction model in critically ill patients
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  76. Model Fusion to Enhance the Clinical Acceptability of Long-Term Glucose Predictions
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  77. Personalized Model Identification for Glucose Dynamics From Clinical Data With Incomplete Inputs
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  78. Physiologically inspired spatiotemporal adaptive multimodal fusion model for blood glucose prediction
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  80. Combining short and long-term models for predicting blood glucose concentrations on diabetic patients
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  84. Interpreting Deep Glucose Predictive Models for Diabetic People Using RETAIN
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  85. Blood Glucose Forecasting using LSTM Variants under the Context of Open Source Artificial Pancreas System
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  86. Using Contextual Information to Improve Blood Glucose Prediction
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  87. Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions
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  92. A strategy based on integer programming for optimal dosing and timing of preventive hypoglycemic treatments in type 1 diabetes management
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