Risk-based postprandial hypoglycemia forecasting using supervised learning.

Journal: International journal of medical informatics
PMID: 31029250

Abstract

BACKGROUND: Predicting insulin-induced postprandial hypoglycemic events is critical for the safety of type 1 diabetes patients because an early warning of hypoglycemia facilitates correction of the insulin bolus before its administration. The postprandial hypoglycemic event counts can be lowered by reducing the size of the bolus based on a reliable prediction but at the cost of increasing the average blood glucose.

Authors

  • Silvia Oviedo
    Institut d'Informatica i Aplicacions. Universitat de Girona, Spain. Electronic address: silvia.oviedo@udg.edu.
  • Ivan Contreras
    Modeling, Identification and Control Laboratory, Institut d'Informatica i Aplicacions, Universitat de Girona, Girona, Spain.
  • Carmen Quirós
    Servicio de Endocrinología y Nutrición. Hospital Universitari Mutua de Terrassa, Terrassa, Spain. Electronic address: cmquiros@clinic.cat.
  • Marga Giménez
    3 Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Faculty of Medicine Imperial College, London, UK.
  • Ignacio Conget
    Diabetes Unit. Endocrinology and Nutrition Dpt. IDIBAPS (Institut d'investigacions biomdiques August Pi I Sunyer), Barcelona, Spain; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Spain. Electronic address: iconget@clinic.cat.
  • Josep Vehi
    Modeling, Identification and Control Laboratory, Institut d'Informatica i Aplicacions, Universitat de Girona, Girona, Spain.

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