Estimating postprandial glucose fluxes using hierarchical Bayes modelling

Computer Methods and Programs in Biomedicine

Volumn 108, Issue 1, 2012, Pages 102-112

  Haidar, Ahmad ^a,d   Potocka, Elizabeth ^b   Boulet, Benoit ^d   Umpleby, A Margot ^c   Hovorka, Roman ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b MannKind Corporation   (United States)

^c UNIVERSITY OF SURREY   (United Kingdom)

^d MCGILL UNIVERSITY   (Canada)

Author keywords

Bayesian estimation; Glucose flux; Glucose tracer; Mathematical modelling; Meal tolerance test

Indexed keywords

BAYESIAN ESTIMATIONS; ENDOGENOUS GLUCOSE; GLUCOSE FLUX; HIERARCHICAL MODEL; MAXIMUM LIKELIHOOD METHODS; MEAL TOLERANCE TEST; ROOT MEAN SQUARE ERRORS; TYPE-2 DIABETES;

BAYESIAN NETWORKS; ESTIMATION; HIERARCHICAL SYSTEMS; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD; MEAN SQUARE ERROR;

GLUCOSE;

GLUCOSE; TRACER; UREA C 13;

ACCURACY; ADULT; ARTICLE; BAYES THEOREM; CLINICAL ARTICLE; CONTROLLED STUDY; FEMALE; GLUCONEOGENESIS; GLUCOSE BLOOD LEVEL; GLUCOSE TOLERANCE TEST; GLUCOSE TRANSPORT; HUMAN; INTERMETHOD COMPARISON; MALE; MAXIMUM LIKELIHOOD METHOD; MEASUREMENT ERROR; NON INSULIN DEPENDENT DIABETES MELLITUS; POSTPRANDIAL STATE; PROBABILITY; RANDOM ERROR; SIMULATION; STOCHASTIC MODEL; TEST MEAL;

BAYES THEOREM; BLOOD GLUCOSE; DIABETES MELLITUS, TYPE 2; HUMANS; LIKELIHOOD FUNCTIONS; MODELS, THEORETICAL; POSTPRANDIAL PERIOD;

EID: 84862526311     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2012.01.010     Document Type: Article

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