Jump neural network for online short-time prediction of blood glucose from continuous monitoring sensors and meal information

Computer Methods and Programs in Biomedicine

Volumn 113, Issue 1, 2014, Pages 144-152

  Zecchin, C ^a   Facchinetti, A ^a   Sparacino, G ^a   Cobelli, C ^a  

^a UNIVERSITY OF PADOVA   (Italy)

Author keywords

Continuous glucose monitoring; Diabetes; Forecast; Non linear modeling; Signal processing; Time series

Indexed keywords

CONTINUOUS GLUCOSE MONITORING; CONTINUOUS GLUCOSEMONITORING (CGM); CONTINUOUS MONITORING; GLUCOSE CONCENTRATION; NON-LINEAR MODEL; PREDICTION PERFORMANCE; SHORT TERM PREDICTION; SHORT-TIME PREDICTIONS;

ALGORITHMS; GLUCOSE; MEDICAL PROBLEMS; NEURAL NETWORKS; PATIENT TREATMENT; SENSORS; SIGNAL PROCESSING; TIME SERIES;

FORECASTING;

CARBOHYDRATE; GLUCOSE;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BLOOD GLUCOSE MONITORING; DIABETIC PATIENT; GLUCOSE BLOOD LEVEL; GLUCOSE SENSOR; INSULIN DEPENDENT DIABETES MELLITUS; MEAL; NERVE CELL NETWORK; NON INSULIN DEPENDENT DIABETES MELLITUS; PREDICTION; SENSOR; SIGNAL PROCESSING; TIME SERIES ANALYSIS;

CONTINUOUS GLUCOSE MONITORING; DIABETES; FORECAST; NON-LINEAR MODELING; SIGNAL PROCESSING; TIME SERIES;

BLOOD GLUCOSE; BLOOD GLUCOSE SELF-MONITORING; DIABETES MELLITUS, TYPE 1; FOOD; HUMANS; NEURAL NETWORKS (COMPUTER);

EID: 84887823309     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2013.09.016     Document Type: Article

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