Using Experimental Data Designs and Multivariate Modeling to Assess the Effect of Glycated Serum Protein Concentration on Glucose Prediction from Near-Infrared Spectra of Human Serum

Applied Spectroscopy

Volumn 68, Issue 4, 2014, Pages 398-405

  Sharma, Sandeep ^a   Goodarzi, Mohammad ^a   Delanghe, Joris ^b   Ramon, Herman ^a   Saeys, Wouter ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b GHENT UNIVERSITY   (Belgium)

Author keywords

Glucose; Glycated serum protein; HbA1c; Human serum; Near infrared spectroscopy; Partial least squares

Indexed keywords

BLOOD; CALIBRATION; FORECASTING; INFRARED DEVICES; LEAST SQUARES APPROXIMATIONS; LINEAR REGRESSION; MEAN SQUARE ERROR; MOLECULES; NEAR INFRARED SPECTROSCOPY; PROTEINS; STATISTICAL TESTS; WATER ABSORPTION;

BLOOD SERUM; CALIBRATION MODEL; GLYCATED SERUM PROTEIN; HBA1C; HUMAN SERUM; NEAR INFRARED SPECTRA; PARTIAL LEAST SQUARES REGRESSION MODELS; PARTIAL LEAST-SQUARES; PROTEIN CONCENTRATIONS; SERUM PROTEINS;

GLUCOSE;

GLUCOSE BLOOD LEVEL; GLYCOSYLATED HEMOGLOBIN;

ANALYSIS; CHEMISTRY; GLUCOSE BLOOD LEVEL; HUMAN; MULTIVARIATE ANALYSIS; NEAR INFRARED SPECTROSCOPY; PROCEDURES; REGRESSION ANALYSIS; ULTRAFILTRATION;

BLOOD GLUCOSE; HEMOGLOBIN A, GLYCOSYLATED; HUMANS; LEAST-SQUARES ANALYSIS; MULTIVARIATE ANALYSIS; SPECTROSCOPY, NEAR-INFRARED; ULTRAFILTRATION;

EID: 84921424781     PISSN: 00037028     EISSN: 19433530     Source Type: Journal    
DOI: 10.1366/13-07217     Document Type: Article

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