The algorithm of stereo vision and shape from shading based on endoscope imaging
With medical endoscopic equipment development, minimally invasive surgery (MIS) has
gradually become an essential technical means in daily medical practice. In recent years …
gradually become an essential technical means in daily medical practice. In recent years …
Glycemic control in the intensive care unit: a control systems perspective
Computers and automation have revolutionised quality and productivity in many industries,
but not in medicine. Healthcare costs are thus growing beyond the ability of society to pay for …
but not in medicine. Healthcare costs are thus growing beyond the ability of society to pay for …
[HTML][HTML] Classification-based deep neural network vs mixture density network models for insulin sensitivity prediction problem
Abstract Model-based glycemic control (GC) protocols are used to treat stress-induced
hyperglycaemia in intensive care units (ICUs). The STAR (Stochastic-TARgeted) glycemic …
hyperglycaemia in intensive care units (ICUs). The STAR (Stochastic-TARgeted) glycemic …
3D kernel-density stochastic model for more personalized glycaemic control: development and in-silico validation
Background The challenges of glycaemic control in critically ill patients have been debated
for 20 years. While glycaemic control shows benefits inter-and intra-patient metabolic …
for 20 years. While glycaemic control shows benefits inter-and intra-patient metabolic …
A systematic stochastic design strategy achieving an optimal tradeoff between peak BGL and probability of hypoglycaemic events for individuals having type 1 …
GC Goodwin, MM Seron, AM Medioli, T Smith… - … Signal Processing and …, 2020 - Elsevier
This paper has two key contributions. The first contribution is a systematic procedure for
fitting an envelope of models which captures a range of possible blood glucose level (BGL) …
fitting an envelope of models which captures a range of possible blood glucose level (BGL) …
Multi-input stochastic prediction of insulin sensitivity for tight glycaemic control using insulin sensitivity and blood glucose data
Background Glycaemic control in the intensive care unit is dependent on effective prediction
of patient insulin sensitivity (SI). The stochastic targeted (STAR) controller uses a 2D …
of patient insulin sensitivity (SI). The stochastic targeted (STAR) controller uses a 2D …
Estimating enhanced endogenous glucose production in intensive care unit patients with severe insulin resistance
A Yahia, Á Szlávecz, JL Knopp… - Journal of Diabetes …, 2022 - journals.sagepub.com
Background: Critically ill ICU patients frequently experience acute insulin resistance and
increased endogenous glucose production, manifesting as stress-induced hyperglycemia …
increased endogenous glucose production, manifesting as stress-induced hyperglycemia …
Risk and reward: extending stochastic glycaemic control intervals to reduce workload
Background STAR is a model-based, personalised, risk-based dosing approach for
glycaemic control (GC) in critically ill patients. STAR provides safe, effective control to nearly …
glycaemic control (GC) in critically ill patients. STAR provides safe, effective control to nearly …
Artificial intelligence based insulin sensitivity prediction for personalized glycaemic control in intensive care
Stress-induced hyperglycaemia is a frequent complication in the intensive therapy that can
be safely and efficiently treated by using the recently developed model-based tight …
be safely and efficiently treated by using the recently developed model-based tight …
Virtual patient trials of a multi-input stochastic model for tight glycaemic control using insulin sensitivity and blood glucose data
Objective Safe, effective glycaemic control (GC) requires accurate prediction of future patient
insulin sensitivity (SI), balancing the risk of hyper-and hypo-glycaemia. The stochastic …
insulin sensitivity (SI), balancing the risk of hyper-and hypo-glycaemia. The stochastic …