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 …
Digital twins and automation of care in the intensive care unit
Healthcare is under increasing demand pressure as societies age and expectations rise,
multiplied by increasing incidence of chronic diseases and decreasing available funding …
multiplied by increasing incidence of chronic diseases and decreasing available funding …
Safety, efficacy and clinical generalization of the STAR protocol: a retrospective analysis
Background The changes in metabolic pathways and metabolites due to critical illness result
in a highly complex and dynamic metabolic state, making safe, effective management of …
in a highly complex and dynamic metabolic state, making safe, effective management of …
A long-term model of the glucose–insulin dynamics of type 1 diabetes
N Magdelaine, L Chaillous, I Guilhem… - IEEE Transactions …, 2015 - ieeexplore.ieee.org
A new glucose-insulin model is introduced which fits with the clinical data from in-and
outpatients for two days. Its stability property is consistent with the glycemia behavior for type …
outpatients for two days. Its stability property is consistent with the glycemia behavior for type …
STAR development and protocol comparison
LM Fisk, AJ Le Compte, GM Shaw… - IEEE Transactions …, 2012 - ieeexplore.ieee.org
Accurate glycemic control (AGC) is difficult due to excessive hypoglycemia risk. Stochastic
TARgeted (STAR) glycemic control forecasts changes in insulin sensitivity to calculate a …
TARgeted (STAR) glycemic control forecasts changes in insulin sensitivity to calculate a …
A simple modeling framework for prediction in the human glucose–insulin system
Forecasting blood glucose (BG) levels with routinely collected data is useful for glycemic
management. BG dynamics are nonlinear, complex, and nonstationary, which can be …
management. BG dynamics are nonlinear, complex, and nonstationary, which can be …
Generalisability of a virtual trials method for glycaemic control in intensive care
Background: Elevated blood glucose (BG) concentrations (Hyperglycaemia) are a common
complication in critically ill patients. Insulin therapy is commonly used to treat …
complication in critically ill patients. Insulin therapy is commonly used to treat …
Untangling glycaemia and mortality in critical care
Background Hyperglycaemia is associated with adverse outcomes in the intensive care unit,
and initial studies suggested outcome benefits of glycaemic control (GC). However …
and initial studies suggested outcome benefits of glycaemic control (GC). However …
Digital twins in critical care: what, when, how, where, why?
Healthcare and intensive care unit (ICU) medicine in particular, are facing a devastating
tsunami of rising demand multiplied by increasing chronic disease and aging demographics …
tsunami of rising demand multiplied by increasing chronic disease and aging demographics …
Mechanistic machine learning: how data assimilation leverages physiologic knowledge using Bayesian inference to forecast the future, infer the present, and …
We introduce data assimilation as a computational method that uses machine learning to
combine data with human knowledge in the form of mechanistic models in order to forecast …
combine data with human knowledge in the form of mechanistic models in order to forecast …