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Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to …
Critical care, like many healthcare areas, is under a dual assault from significantly
increasing demographic and economic pressures. Intensive care unit (ICU) patients are …
increasing demographic and economic pressures. Intensive care unit (ICU) patients are …
Convolutional recurrent neural networks for glucose prediction
Control of blood glucose is essential for diabetes management. Current digital therapeutic
approaches for subjects with type 1 diabetes mellitus such as the artificial pancreas and …
approaches for subjects with type 1 diabetes mellitus such as the artificial pancreas and …
Combining continuous glucose monitoring and insulin pumps to automatically tune the basal insulin infusion in diabetes therapy: a review
For individuals affected by Type 1 diabetes (T1D), a chronic disease in which the pancreas
does not produce any insulin, maintaining the blood glucose (BG) concentration as much as …
does not produce any insulin, maintaining the blood glucose (BG) concentration as much as …
Stacked LSTM based deep recurrent neural network with kalman smoothing for blood glucose prediction
Background Blood glucose (BG) management is crucial for type-1 diabetes patients
resulting in the necessity of reliable artificial pancreas or insulin infusion systems. In recent …
resulting in the necessity of reliable artificial pancreas or insulin infusion systems. In recent …
GluNet: A deep learning framework for accurate glucose forecasting
For people with Type 1 diabetes (T1D), forecasting of blood glucose (BG) can be used to
effectively avoid hyperglycemia, hypoglycemia and associated complications. The latest …
effectively avoid hyperglycemia, hypoglycemia and associated complications. The latest …
Deep multitask learning by stacked long short-term memory for predicting personalized blood glucose concentration
The adverse glycemic events triggered by the inaccurate insulin infusion in Type I diabetes
(T1D) can lead to fatal complications. Predicting blood glucose concentration (BGC) based …
(T1D) can lead to fatal complications. Predicting blood glucose concentration (BGC) based …
[KSIĄŻKA][B] Introduction to modeling in physiology and medicine
C Cobelli, E Carson - 2019 - books.google.com
Introduction to Modeling in Physiology and Medicine, Second Edition, develops a clear
understanding of the fundamental principles of good modeling methodology. Sections show …
understanding of the fundamental principles of good modeling methodology. Sections show …
An autonomous channel deep learning framework for blood glucose prediction
T Yang, X Yu, N Ma, R Wu, H Li - Applied Soft Computing, 2022 - Elsevier
Accurate prediction of blood glucose (BG) is conducive to avoiding abnormal blood glucose
events and improving blood glucose management for Type 1 diabetes (T1D) patients …
events and improving blood glucose management for Type 1 diabetes (T1D) patients …
Machine-learning based model to improve insulin bolus calculation in type 1 diabetes therapy
Objective: This paper aims at proposing a new machine-learning based model to improve
the calculation of mealtime insulin boluses (MIB) in type 1 diabetes (T1D) therapy using …
the calculation of mealtime insulin boluses (MIB) in type 1 diabetes (T1D) therapy using …
Personalized blood glucose prediction: A hybrid approach using grammatical evolution and physiological models
The large patient variability in human physiology and the effects of variables such as
exercise or meals challenge current prediction modeling techniques. Physiological models …
exercise or meals challenge current prediction modeling techniques. Physiological models …