Blood glucose level prediction using physiological models and support vector regression

Proceedings - 2013 12th International Conference on Machine Learning and Applications, ICMLA 2013

Volumn 1, Issue , 2013, Pages 135-140

  Bunescu, Razvan ^a   Struble, Nigel ^a   Marling, Cindy ^a   Shubrook, Jay ^b   Schwartz, Frank ^b  

^a US Institute of Navigation   (United States)

^b OHIO UNIVERSITY   (United States)

Author keywords

diabetes; regression; time series forecasting

Indexed keywords

FORECASTING; GLUCOSE; INSULIN; LEARNING SYSTEMS; MATHEMATICAL MODELS; MEDICAL PROBLEMS; PHYSIOLOGICAL MODELS; PHYSIOLOGY; REGRESSION ANALYSIS;

AUTOMATIC PREDICTION; BLOOD GLUCOSE LEVEL; MACHINE LEARNING MODELS; PHYSIOLOGICAL FEATURES; REGRESSION; SUPPORT VECTOR REGRESSION (SVR); SUPPORT VECTOR REGRESSION MODELS; TIME SERIES FORECASTING;

BLOOD;

EID: 84899450573     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLA.2013.30     Document Type: Conference Paper

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