Application of partial least squares near-infrared spectral classification in diabetic identification

Wen-juan Yan; Ming Yang; Guo-quan He; Lin Qin; Gang Li

doi:10.1117/12.2070592

20 November 2014 Application of partial least squares near-infrared spectral classification in diabetic identification

Wen-juan Yan, Ming Yang, Guo-quan He, Lin Qin, Gang Li

Proceedings Volume 9300, International Symposium on Optoelectronic Technology and Application 2014: Infrared Technology and Applications; 93000G (2014) https://doi.org/10.1117/12.2070592
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China

Abstract

In order to identify the diabetic patients by using tongue near-infrared (NIR) spectrum，a spectral classification model of the NIR reflectivity of the tongue tip is proposed, based on the partial least square (PLS) method. 39sample data of tongue tip’s NIR spectra are harvested from healthy people and diabetic patients , respectively. After pretreatment of the reflectivity, the spectral data are set as the independent variable matrix, and information of classification as the dependent variables matrix, Samples were divided into two groups，i.e. 53 samples as calibration set and 25 as prediction set，then the PLS is used to build the classification model The constructed modelfrom the 53 samples has the correlation of 0.9614 and the root mean square error of cross-validation (RMSECV) of 0.1387.The predictions for the 25 samples have the correlation of 0.9146 and the RMSECV of 0.2122.The experimental result shows that the PLS method can achieve good classification on features of healthy people and diabetic patients.

Citation Download Citation

Wen-juan Yan, Ming Yang, Guo-quan He, Lin Qin, and Gang Li "Application of partial least squares near-infrared spectral classification in diabetic identification", Proc. SPIE 9300, International Symposium on Optoelectronic Technology and Application 2014: Infrared Technology and Applications, 93000G (20 November 2014); https://doi.org/10.1117/12.2070592

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available