Related references
Note: Only part of the references are listed.Improvement of K-means Cluster Quality by Post Processing Resulted Clusters
Ioan-Daniel Borlea et al.
8TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT (ITQM 2020 & 2021): DEVELOPING GLOBAL DIGITAL ECONOMY AFTER COVID-19 (2022)
In silico trials: Verification, validation and uncertainty quantification of predictive models used in the regulatory evaluation of biomedical products
Marco Viceconti et al.
METHODS (2021)
Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges
DonHee Lee et al.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2021)
Evaluation of stochastic and artificial intelligence models in modeling and predicting of river daily flow time series
Pouya Aghelpour et al.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2020)
The use of mixture density networks in the emulation of complex epidemiological individual-based models
Christopher N. Davis et al.
PLoS Computational Biology (2020)
A multi-class classification model for supporting the diagnosis of type II diabetes mellitus
Kuang-Ming Kuo et al.
PEERJ (2020)
Glycemic control in the intensive care unit: A control systems perspective
J. Geoffrey Chase et al.
ANNUAL REVIEWS IN CONTROL (2019)
3D kernel-density stochastic model for more personalized glycaemic control: development and in-silico validation
Vincent Uyttendaele et al.
BIOMEDICAL ENGINEERING ONLINE (2019)
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 validation them
J. Geoffrey Chase et al.
BIOMEDICAL ENGINEERING ONLINE (2018)
Generalisability of a Virtual Trials Method for Glycaemic Control in Intensive Care
Jennifer L. Dickson et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2018)
A 3D insulin sensitivity prediction model enables more patient-specific prediction and model-based glycaemic control
Vincent Uyttendaele et al.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2018)
Untangling glycaemia and mortality in critical care
Vincent Uyttendaele et al.
CRITICAL CARE (2017)
Safety, efficacy and clinical generalization of the STAR protocol: a retrospective analysis
Kent W. Stewart et al.
ANNALS OF INTENSIVE CARE (2016)
Stochastic Simulation and Parameter Estimation of the ICING Model
Bela Palancz et al.
IFAC PAPERSONLINE (2016)
Clinical review: Consensus recommendations on measurement of blood glucose and reporting glycemic control in critically ill adults
Simon Finfer et al.
CRITICAL CARE (2013)
Pilot study of a model-based approach to blood glucose control in very-low-birthweight neonates
Aaron J. Le Compte et al.
BMC PEDIATRICS (2012)
Variability of insulin sensitivity during the first 4 days of critical illness: implications for tight glycemic control
Christopher G. Pretty et al.
ANNALS OF INTENSIVE CARE (2012)
Modeling the glucose regulatory system in extreme preterm infants
Aaron Le Compte et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2011)
Tight glycemic control in critical care - The leading role of insulin sensitivity and patient variability: A review and model-based analysis
J. Geoffrey Chase et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2011)
A physiological Intensive Control Insulin-Nutrition-Glucose (ICING) model validated in critically ill patients
Jessica Lin et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2011)
Validation of a model-based virtual trials method for tight glycemic control in intensive care
J. Geoffrey Chase et al.
BIOMEDICAL ENGINEERING ONLINE (2010)
Organ failure and tight glycemic control in the SPRINT study
J. Geoffrey Chase et al.
CRITICAL CARE (2010)
Stochastic modelling of insulin sensitivity and adaptive glycemic control for critical care
Jessica Lin et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2008)
Glucose variability and mortality in patients with sepsis
Naeem A. Ali et al.
CRITICAL CARE MEDICINE (2008)
Implementation and evaluation of the SPRINT protocol for tight glycaemic control in critically ill patients: a clinical practice change
J. Geoffrey Chase et al.
CRITICAL CARE (2008)
Effect of intensive insulin therapy on insulin sensitivity in the critically ill
Lies Langouche et al.
JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM (2007)
Intensive insulin protocol improves glucose control and is associated with a reduction in intensive care unit mortality
Charles C. Reed et al.
JOURNAL OF THE AMERICAN COLLEGE OF SURGEONS (2007)
The use of artificial neural networks in decision support in cancer: A systematic review
Paulo J. Lisboa et al.
NEURAL NETWORKS (2006)
A simple insulin-nutrition protocol for tight glycemic control in critical illness: Development and protocol comparison
Timothy Lonergan et al.
DIABETES TECHNOLOGY & THERAPEUTICS (2006)
Integral-based parameter identification for long-term dynamic verification of a glucose-insulin system model
CE Hann et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2005)
Effect of an intensive glucose management protocol on the mortality of critically ill adult patients
JS Krinsley
MAYO CLINIC PROCEEDINGS (2004)
Integrating model-based decision support in a multi-modal reasoning system for managing type 1 diabetic patients
S Montani et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2003)
Intensive insulin therapy in critically ill patients.
G Van den Berghe et al.
NEW ENGLAND JOURNAL OF MEDICINE (2001)
Stress-induced hyperglycemia
KC McCowen et al.
CRITICAL CARE CLINICS (2001)
Share Paper
