Meal Simulation Model of the Glucose-Insulin System

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Items 101–200 of 955

1. Robust Fault Detection System for Insulin Pump Therapy Using Continuous Glucose Monitoring
   Herrero, Pau, Calm, Remei, Vehí, Josep, Armengol, Joaquim, Georgiou, Pantelis, Oliver, Nick, Tomazou, Christofer · 2012 · Journal of Diabetes Science and Technology
2. Real-time insulin bolusing for unannounced meals with artificial pancreas
   Kamuran Turksoy, Iman Hajizadeh, Sediqeh Samadi, Jianyuan Feng, Mert Sevil, Minsun Park, Laurie Quinn, Elizabeth Littlejohn, Ali Çınar · 2016 · Control Engineering Practice
3. Model-based falsification of an artificial pancreas control system
   Sriram Sankaranarayanan, Suhas Akshar Kumar, Faye M. Cameron, B. Wayne Bequette, Georgios Fainekos, David M. Maahs · 2017 · ACM SIGBED Review
4. Plasma Insulin Estimation in People with Type 1 Diabetes Mellitus
   Iman Hajizadeh, Mudassir Mohammad Rashid, Kamuran Turksoy, Sediqeh Samadi, Jianyuan Feng, Nicole Hobbs, Mert Sevil, Eda Cengiz, Ali Çınar · 2017 · Industrial & Engineering Chemistry Research
5. Acute Effects of Morning Light on Plasma Glucose and Triglycerides in Healthy Men and Men with Type 2 Diabetes
   R. Versteeg, D. Stenvers, Dana Visintainer, Andre Linnenbank, M. Tanck, G. Zwanenburg, A. Smilde, E. Fliers, A. Kalsbeek, M. Serlie et al. · 2017 · Journal of Biological Rhythms
6. Simulation models for in silico testing of closed-loop glucose controllers in type 1 diabetes
   M. Wilińska, R. Hovorka · 2008 · Drug Discovery Today Disease Models
7. A Pharmacokinetic Model of a Tissue Implantable Insulin Sensor
   Gili Bisker, Nicole M. Iverson, Jiyoung Ahn, Michael S. Strano · 2014 · Advanced Healthcare Materials
8. A Universal Approximation Result for Difference of Log-Sum-Exp Neural Networks
   Giuseppe C. Calafiore, Stéphane Gaubert, Corrado Possieri · 2020 · IEEE Transactions on Neural Networks and Learning Systems
9. Internal model sliding mode control approach for glucose regulation in type 1 diabetes
   Amjad Abu-Rmileh, Winston García-Gabín, Darine Zambrano · 2010 · Biomedical Signal Processing and Control
10. Reduction of Number and Duration of Hypoglycemic Events by Glucose Prediction Methods: A Proof-of-Concept In Silico Study
    Chiara Zecchin, Andrea Facchinetti, Giovanni Sparacino, Claudio Cobelli · 2013 · Diabetes Technology & Therapeutics
11. Wearable systems and mobile applications for diabetes disease management
    Eleni I. Georga, Vasilios C. Protopappas, Christos V. Bellos, Dimitrios I. Fotiadis · 2014 · Health and Technology
12. Advancing Our Understanding of the Glucose System via Modeling: A Perspective
    Cobelli, Claudio, Dalla Man, Chiara, Pedersen, Morten Gram, Bertoldo, Alessandra, Toffolo, Gianna · 2014 · IEEE Transactions on Biomedical Engineering
13. Analysis of three T1DM simulation models for evaluating robust closed-loop controllers
    Patricio H. Colmegna, Ricardo Sánchez‐Peña · 2013 · Computer Methods and Programs in Biomedicine
14. Postprandial blood glucose control using a hybrid adaptive PD controller with insulin-on-board limitation
    Fabian Mauricio León Vargas, Fabricio Garelli, Hernán De Battista, Josep Vehı́ · 2013 · Biomedical Signal Processing and Control
15. Automated meal detection from continuous glucose monitor data through simulation and explanation
    Min Zheng, Baohua Ni, Samantha Kleinberg · 2019 · Journal of the American Medical Informatics Association
16. Developing the UVA/Padova Type 1 Diabetes Simulator: Modeling, Validation, Refinements, and Utility
    Cobelli, Claudio, Kovatchev, Boris · 2023 · Journal of Diabetes Science and Technology
17. Estimating Interval Process Models for Type 1 Diabetes for Robust Control Design
    Harald Kirchsteiger, Giovanna Castillo Estrada, Stephan Pölzer, Éric Renard, Luigi del Re · 2011 · IFAC Proceedings Volumes
18. Optimal Design of Clinical Tests for the Identification of Physiological Models of Type 1 Diabetes Mellitus
    Federico Galvanin, Massimiliano Barolo, Sandro Macchietto, Fabrizio Bezzo · 2009 · Industrial & Engineering Chemistry Research
19. Method for automatic adjustment of an insulin bolus calculator: In silico robustness evaluation under intra-day variability
    Herrero, Pau, Pesl, Peter, Bondia, Jorge, Reddy, Monika, Oliver, Nick, Georgiou, Pantelis, Toumazou, Christofer · 2015 · Computer Methods and Programs in Biomedicine
20. A pathway model of glucose-stimulated insulin secretion in the pancreatic β-cell
    M. Deepa Maheshvare, Soumyendu Raha, Matthias König, Debnath Pal · 2023 · Frontiers in Endocrinology
21. Integration not isolation: arguing the case for quantitative and systems pharmacology in drug discovery and development
    Balaji M. Agoram, Oleg O Demin · 2011 · Drug Discovery Today
22. An adaptive backstepping based non-linear controller for artificial pancreas in type 1 diabetes patients
    Iftikhar Ahmad, Faysal Munir, Muhammad Faizan Munir · 2018 · Biomedical Signal Processing and Control
23. After-meal blood glucose level prediction using an absorption model for neural network training
    Rebaz A. H. Karim, István Vassányi, István Kósa · 2020 · Computers in Biology and Medicine
24. A molecular mathematical model of glucose mobilization and uptake.
    Wei-Jiu Liu, Ching-Mei Hsin, Fusheng Tang · 2009 · Mathematical Biosciences
25. Model predictive control with learning‐type set‐point: Application to artificial pancreatic β‐cell
    Youqing Wang, Howard Zisser, Eyal Dassau, Lois G. Jovanovic, Francis J. Doyle · 2009 · AIChE Journal
26. Ongoing β-Cell Turnover in Adult Nonhuman Primates Is Not Adaptively Increased in Streptozotocin-Induced Diabetes
    Y. Saisho, E. Manesso, A. Butler, R. Galasso, K. Kavanagh, Mickey Flynn, Li Zhang, Paige B. Clark, T. Gurlo, G. Toffolo et al. · 2011 · Diabetes
27. Model-based analysis of postprandial glycemic response dynamics for different types of food
    Y. Rozendaal, A. Maas, C. van Pul, E. Cottaar, H. Haak, P. Hilbers, N. van Riel · 2018 · Clinical Nutrition Experimental
28. Model Predictive Control of glucose concentration in subjects with type 1 diabetes: an in silico trial
    L. Magni, D. Raimondo, C. Man, G. De Nicolao, B. Kovatchev, C. Cobelli · 2008 · IFAC Proceedings Volumes
29. Knockout mouse models of insulin signaling: Relevance past and future
    Anne E. Bunner, P. Charukeshi Chandrasekera, Neal D. Barnard · 2014 · World Journal of Diabetes
30. Physiological Models and Control for Type 1 Diabetes Mellitus: A Brief Review
    A. Nath, S. Biradar, A. Balan, R. Dey, R. Padhi · 2018 · IFAC-PapersOnLine
31. A DISCRETE-TIME RECURRENT NEUROFUZZY NETWORK FOR BLACK-BOX MODELING OF INSULIN DYNAMICS IN DIABETIC TYPE-1 PATIENTS
    Marcos Angel Gonzalez-Olvera, Ana Gabriela Gallardo-Hernández, Yu Qing Tang, M. Revilla, Sergio Islas‐Andrade · 2010 · International Journal of Neural Systems
32. Continuous-time interval model identification of blood glucose dynamics for type 1 diabetes
    Harald Kirchsteiger, Rolf Johansson, Éric Renard, Luigi del Re · 2014 · International Journal of Control
33. Long-Term Glucose Forecasting Using a Physiological Model and Deconvolution of the Continuous Glucose Monitoring Signal
    Chengyuan Liu, J. Vehí, P. Avari, M. Reddy, N. Oliver, P. Georgiou, P. Herrero · 2019 · Italian National Conference on Sensors
34. The Padova Type 2 Diabetes Simulator from Triple-Tracer Single-Meal Studies: In Silico Trials Also Possible in Rare but Not-So-Rare Individuals
    ROBERTO VISENTIN, Claudio Cobelli, Chiara Dalla Man · 2020 · Diabetes Technology & Therapeutics
35. AP@home: A Novel European Approach to Bring the Artificial Pancreas Home
    Lutz Heinemann, Carsten Benesch, J. Hans DeVries · 2011 · Journal of Diabetes Science and Technology
36. Insulin signaling – mathematical modeling comes of age
    Nyman, Elin, Cedersund, Gunnar, Strålfors, Peter · 2012 · Trends in Endocrinology & Metabolism
37. Neural network-based model predictive control for type 1 diabetic rats on artificial pancreas system
    Saeid Bahremand, H. Ko, Ramin Balouchzadeh, H. F. Lee, Sarah Park, Guim Kwon · 2018 · Medical and Biological Engineering and Computing
38. CausalBG: Causal Recurrent Neural Network for the Blood Glucose Inference With IoT Platform
    Miao He, Weixi Gu, Ying Kong, Lin Zhang, Costas J. Spanos, Khalid M. Mosalam · 2019 · IEEE Internet of Things Journal
39. Blood-Glucose Regulation Using Fractional-Order PID Control
    Henrique Mohallem Paiva, Keller Wagner Souza, Luísa Garcia Ribeiro da Cunha · 2019 · Journal of Control Automation and Electrical Systems
40. Glucose Prediction in Type 1 and Type 2 Diabetic Patients Using Data Driven Techniques
    I Georga Eleni, C. Vasilios, I Fotiadis Dimitrios · 2011 · InTech eBooks
41. Computational modelling of the regulation of Insulin signalling by oxidative stress
    Graham R. Smith, Daryl P. Shanley · 2013 · BMC Systems Biology
42. Modeling and Control of Diabetes: Towards the Artificial Pancreas
    Giuseppe De Nicolao, Lalo Magni, Chiara Dalla Man, Claudio Cobelli · 2011 · IFAC Proceedings Volumes
43. Brief history and future of animal simulation models for science and application
    John L. Black · 2014 · Animal Production Science
44. Quantitative Systems Pharmacology Modeling of Acid Sphingomyelinase Deficiency and the Enzyme Replacement Therapy Olipudase Alfa Is an Innovative Tool for Linking Pathophysiology and Pharmacology
    Kaddi, Chanchala D., Niesner, Bradley, Baek, Rena, Jasper, Paul, Pappas, John, Tolsma, John, Li, Jing, van Rijn, Zachary, Tao, Mengdi, Ortemann‐Renon, Catherine et al. · 2018 · CPT: Pharmacometrics & Systems Pharmacology
45. Digital twin predicting diet response before and after long-term fasting
    Oscar Silfvergren, C. Simonsson, M. Ekstedt, P. Lundberg, Peter Gennemark, G. Cedersund · 2021 · bioRxiv
46. Model-based control of plasma glycemia: Tests on populations of virtual patients.
    P. Palumbo, G. Pizzichelli, S. Panunzi, P. Pepe, A. De Gaetano · 2014 · Mathematical Biosciences
47. Contradiction Resolution in the Adaptive Control of Underactuated Mechanical Systems Evading the Framework of Optimal Controllers
    2016 · Acta Polytechnica Hungarica
48. GLYFE: review and benchmark of personalized glucose predictive models in type 1 diabetes
    Maxime De Bois, M. El Yacoubi, M. Ammi · 2020 · Medical and Biological Engineering and Computing
49. Modeling the physiological glucose-insulin dynamic system on diabetics.
    Cheng-Liang Chen, Hong-Wen Tsai, S. Wong · 2010 · Journal of Theoretical Biology
50. Replay Simulations with Personalized Metabolic Model for Treatment Design and Evaluation in Type 1 Diabetes
    Hughes, Jonathan, Gautier, Thibault, Colmegna, Patricio, Fabris, Chiara, Breton, Marc D · 2021 · Journal of Diabetes Science and Technology
51. Modeling impulsive insulin delivery in insulin pump with time delays
    Song, Xinyu, Huang, Mingzhan, Li, Jiaxu · 2014 · SIAM Journal on Applied Mathematics
52. In Silico Closed-Loop Control Validation Studies for Optimal Insulin Delivery in Type 1 Diabetes
    Stamatina Zavitsanou, Athanasios Mantalaris, Michael C. Georgiadis, Efstratios N. Pistikopoulos · 2015 · IEEE Transactions on Biomedical Engineering
53. Mathematical modelling of hepatic lipid metabolism.
    Adrian Pratt, J. Wattis, A. Salter · 2015 · Mathematical Biosciences
54. Stable impulsive zone model predictive control for type 1 diabetic patients based on a long‐term model
    Alejandro H. González, Pablo S. Rivadeneira, Antonio Ferramosca, Nicolas Magdelaine, Claude H. Moog · 2020 · Optimal Control Applications and Methods
55. Bayesian metamodeling of complex biological systems across varying representations
    Barak Raveh, Liping Sun, Kate L. White, Tanmoy Sanyal, Jeremy O. B. Tempkin, Dongqing Zheng, Kala Bharath, Jitin Singla, Chenxi Wang, Jihui Zhao et al. · 2021 · Proceedings of the National Academy of Sciences
56. Inverse optimal neural control of blood glucose level for type 1 diabetes mellitus patients
    Blanca S. Leon, A. Alanis, E. Sánchez, Fernando Ornelas-Tellez, E. Ruiz‐Velázquez · 2012 · Journal of the Franklin Institute
57. Overnight Control of Blood Glucose in People with Type 1 Diabetes
    Dimitri Boiroux, Anne Katrine Duun‐Henriksen, Signe Schmidt, Kirsten Nørgaard, Sten Madsbad, Ole Skyggebjerg, Peter Ruhdal Jensen, Niels Kjølstad Poulsen, Henrik Madsen, John Bagterp Jørgensen · 2012 · IFAC Proceedings Volumes
58. Anticipating the next meal using meal behavioral profiles: A hybrid model-based stochastic predictive control algorithm for T1DM
    Colleen S. Hughes, S. Patek, M. Breton, B. Kovatchev · 2010 · Comput. Methods Programs Biomed.
59. Impulsive Zone MPC for Type I Diabetic Patients based on a long-term model
    Alejandro H. González, Pablo S. Rivadeneira, Antonio Ferramosca, Nicolas Magdelaine, Claude H. Moog · 2017 · IFAC-PapersOnLine
60. Diabetes Technology: Markers, Monitoring, Assessment, and Control of Blood Glucose Fluctuations in Diabetes
    B. Kovatchev · 2012 · Scientifica
61. A Gain-Scheduling Model Predictive Controller for Blood Glucose Control in Type 1 Diabetes
    Amjad Abu-Rmileh, Winston García-Gabín · 2009 · IEEE Transactions on Biomedical Engineering
62. Putting the pieces together in diabetes research: towards a hierarchical model of whole-body glucose homeostasis.
    G. Cedersund, P. Strålfors · 2009 · European Journal of Pharmaceutical Sciences
63. A therapy parameter-based model for predicting blood glucose concentrations in patients with type 1 diabetes
    A. Bock, G. François, D. Gillet · 2015 · Comput. Methods Programs Biomed.
64. A coordinated control strategy for insulin and glucagon delivery in type 1 diabetes
    Pau Herrero, Jorge Bondía, Nick S. Oliver, Pantelis Georgiou · 2017 · Computer Methods in Biomechanics & Biomedical Engineering
65. An augmented subcutaneous type 1 diabetic patient modelling and design of adaptive glucose control
    Anirudh Nath, Dipankar Deb, Rajeeb Dey · 2020 · Journal of Process Control
66. Direct continuous time system identification of MISO transfer function models applied to type 1 diabetes
    Harald Kirchsteiger, Stephan Pölzer, Rolf Johansson, Éric Renard, Luigi del Re · 2011 · IEEE Conference on Decision and Control (CDC)
67. Closed-Loop Control and Advisory Mode Evaluation of an Artificial Pancreatic β Cell: Use of Proportional-Integral-Derivative Equivalent Model-Based Controllers
    M. W. Percival, H. Zisser, L. Jovanovic, F. Doyle · 2008 · Journal of Diabetes Science and Technology
68. Modeling of glucose regulation and insulin-signaling pathways.
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69. Siphon Effects on Continuous Subcutaneous Insulin Infusion Pump Delivery Performance
    Howard Zisser, Wendy C. Bevier, Eyal Dassau, Lois Jovanovič · 2010 · Journal of Diabetes Science and Technology
70. Reduction in Intrasubject Variability in the Pharmacokinetic Response to Insulin After Subcutaneous Co-Administration with Recombinant Human Hyaluronidase in Healthy Volunteers
    Linda Morrow, Douglas B. Muchmore, Elizabeth A. Ludington, Daniel E. Vaughn, Marcus Hompesch · 2011 · Diabetes Technology & Therapeutics
71. Robust PBPK/PD-Based Model Predictive Control of Blood Glucose
    Stephan Schaller, Jörg Lippert, Lukas A. Schaupp, Thomas Rudolf Pieber, Andreas Schuppert, Thomas Eißing · 2015 · IEEE Transactions on Biomedical Engineering
72. An Information Theoretical Analysis of Human Insulin-Glucose System Toward the Internet of Bio-Nano Things
    Naveed Ahmed Abbasi, Özgür B. Akan · 2017 · IEEE Transactions on NanoBioscience
73. Robust Sliding Mode Closed-loop Glucose Control with Meal Compensation in Type 1 Diabetes Mellitus
    W. García-Gabín, J. Vehí, J. Bondia, C. Tarín, Remei Calm · 2008 · IFAC Proceedings Volumes
74. Simulating Insulin Infusion Pump Risks by In-Silico Modeling of the Insulin-Glucose Regulatory System
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75. Towards a Verified Artificial Pancreas: Challenges and Solutions for Runtime Verification
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76. Variables to Be Monitored via Biomedical Sensors for Complete Type 1 Diabetes Mellitus Management: An Extension of the “On-Board” Concept
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77. Understanding drugs and diseases by systems biology?
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78. An Enhanced Model Predictive Control for the Artificial Pancreas Using a Confidence Index Based on Residual Analysis of Past Predictions
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79. Multivariable Recursive Subspace Identification with Application to Artificial Pancreas Systems
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80. Bernoulli wavelet method for non-linear fractional Glucose–Insulin regulatory dynamical system
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81. Individualized Models for Glucose Prediction in Type 1 Diabetes: Comparing Black-Box Approaches to a Physiological White-Box One
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82. Physiological analysis on oscillatory behavior of glucose-insulin regulation by model with delays.
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83. NEFA minimal model parameters estimated from the oral glucose tolerance test and the meal tolerance test
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84. A robust sliding mode controller with internal model for closed-loop artificial pancreas
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85. Regulation of blood glucose concentration in type 1 diabetics using single order sliding mode control combined with fuzzy on-line tunable gain, a simulation study
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86. Digital Twins in Type 1 Diabetes: A Systematic Review
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87. Sampled-data Observer-based Glucose Control for the Artificial Pancreas
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88. A generic telemedicine infrastructure for monitoring an artificial pancreas trial
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89. Linear Model Identification for Personalized Prediction and Control in Diabetes
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90. Personalized glucose-insulin metabolism model based on self-organizing maps for patients with Type 1 Diabetes Mellitus
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91. Semiglobal Sampled-Data Dynamic Output Feedback Controller for the Glucose–Insulin System
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92. A Quantitative Systems Pharmacology Model of Gaucher Disease Type 1 Provides Mechanistic Insight Into the Response to Substrate Reduction Therapy With Eliglustat
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93. A comparison among three maximal mathematical models of the glucose-insulin system
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94. A multi-scale digital twin for adiposity-driven insulin resistance in humans: diet and drug effects
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95. A Physiology-Based Model Describing Heterogeneity in Glucose Metabolism
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96. A Model for the Estimation of Hepatic Insulin Extraction After a Meal
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97. Quantized sampled-data static output feedback control of the glucose–insulin system
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98. Effect of BGM Accuracy on the Clinical Performance of CGM: An In-Silico Study
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99. Mapping data to virtual patients in type 1 diabetes
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100. Applications of the Internet of Medical Things to Type 1 Diabetes Mellitus
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