Accurate prediction of continuous blood glucose based on support vector regression and differential evolution algorithm

Biocybernetics and Biomedical Engineering

Volumn 38, Issue 2, 2018, Pages 362-372

  Hamdi, Takoua ^a,b   Ben Ali, Jaouher ^a   Di Costanzo, Véronique ^c   Fnaiech, Farhat ^a   Moreau, Eric ^b   Ginoux, Jean Marc ^b  

^a UNIVERSITY OF TUNIS   (Tunisia)

^b UNIVERSITÉ DE TOULON   (France)

^c Centre Hospitalier Intercommunal Toulon La Seyne sur Mer   (France)

Author keywords

Continuous glucose monitoring (CGM); Differential evolution (DE); Support vector regression (SVR); Time series forecasting; Type 1 diabetes (T1D)

Indexed keywords

GLUCOSE;

ALGORITHM; ARTICLE; BLOOD GLUCOSE MONITORING; HUMAN; INSULIN DEPENDENT DIABETES MELLITUS; MEASUREMENT ACCURACY; PREDICTION; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE;

EID: 85044099313     PISSN: 02085216     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.bbe.2018.02.005     Document Type: Article

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