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Accuracy and optimization of a subcutaneous insulin model for less acute critical care patients.

, , , , , , and . EMBC, page 4435-4438. IEEE, (2015)

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External validation and sub-cohort analysis of stochastic forecasting models in NICU cohorts., , , , , , and . Biomed. Signal Proc. and Control, 8 (4): 409-419 (2013)A virtual patient model for mechanical ventilation., , , , , , , and . Computer Methods and Programs in Biomedicine, (2018)Generalisability of a Virtual Trials Method for Glycaemic Control in Intensive Care., , , , , , , , , and . IEEE Trans. Biomed. Engineering, 65 (7): 1543-1553 (2018)Development and optimisation of stochastic targeted (STAR) glycaemic control for pre-term infants in neonatal intensive care., , , , , and . Biomed. Signal Proc. and Control, 8 (2): 215-221 (2013)Accuracy and optimization of a subcutaneous insulin model for less acute critical care patients., , , , , , and . EMBC, page 4435-4438. IEEE, (2015)Brain mass estimation by head circumference and body mass methods in neonatal glycaemic modelling and control., , , , , , and . Computer Methods and Programs in Biomedicine, 115 (2): 47-54 (2014)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, , , , , , , , , and 3 other author(s). BioMedical Engineering OnLine, (February 2018)Evaluation of a plasma insulin model for glycaemic control in intensive care., , , , , and . EMBC, page 4009-4012. IEEE, (2015)