Raman spectroscopy and PCA-SVM as a non-invasive diagnostic tool to identify and classify qualitatively glycated hemoglobin levels in vivo

Journal of Biophotonics

Volumn 10, Issue 8, 2017, Pages 1074-1079

  Villa Manriquez J F ^a   Castro Ramos, J ^a   Gutierrez Delgado F ^b   Lopez Pacheco M A ^a   Villanueva Luna, A E ^c  

^a INSTITUTO NACIONAL DE ASTROFÍSICA   (Mexico)

^b Ctro Estud y Prevencion del Cancer   (Mexico)

^c Universidad Tecnológica de Campeche   (Mexico)

Author keywords

Biomedical application; medicine; spectroscopy

Indexed keywords

DATA HANDLING; DIAGNOSTIC PRODUCTS; HEMOGLOBIN; MACHINE COMPONENTS; MEDICAL APPLICATIONS; MEDICINE; NONINVASIVE MEDICAL PROCEDURES; PRINCIPAL COMPONENT ANALYSIS; RAMAN SPECTROSCOPY; SPECTROSCOPY; SUPPORT VECTOR MACHINES;

ANATOMICAL REGIONS; BIOMEDICAL APPLICATIONS; DIAGNOSTIC ALGORITHMS; GLYCATED HEMOGLOBIN (HBA1C); GLYCATED HEMOGLOBINS; NON-INVASIVE DIAGNOSTICS; PRINCIPAL COMPONENTS ANALYSIS; RECEIVER OPERATING CHARACTERISTIC CURVES;

DIAGNOSIS;

GLYCOSYLATED HEMOGLOBIN;

ALGORITHM; BLOOD; CASE CONTROL STUDY; DIABETES MELLITUS; HUMAN; PRINCIPAL COMPONENT ANALYSIS; RAMAN SPECTROMETRY; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE;

ALGORITHMS; CASE-CONTROL STUDIES; DIABETES MELLITUS; GLYCATED HEMOGLOBIN A; HUMANS; PRINCIPAL COMPONENT ANALYSIS; SENSITIVITY AND SPECIFICITY; SPECTRUM ANALYSIS, RAMAN; SUPPORT VECTOR MACHINE;

EID: 85007409112     PISSN: 1864063X     EISSN: 18640648     Source Type: Journal    
DOI: 10.1002/jbio.201600169     Document Type: Article

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