{"title":"Near Infrared Spectroscopy (NIRs) applications in medical: Non-invasive and invasive leukemia screening","authors":"Ruhaizan Ismail, H. A. Rahim","doi":"10.1109/CSPA.2016.7515851","DOIUrl":null,"url":null,"abstract":"Near Infrared Spectroscopy (NIRs) has been applied as analytical tool in numerous field of study due to its ability in noninvasive application. This paper proposed a non-invasive method in early screening of leukemia using NIRS. In this method NIRs is applied directly at human fingertip for spectral data acquisition and standard blood test procedure which involve blood draw is done for laboratory data acquisition. The prediction model will compared the spectral data with laboratory data for validation. The performance of PCR and PLSR prediction model is compared for the selection of model with high accuracy level. PLSR shows a better performance compared to PCR.","PeriodicalId":314829,"journal":{"name":"2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSPA.2016.7515851","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Near Infrared Spectroscopy (NIRs) has been applied as analytical tool in numerous field of study due to its ability in noninvasive application. This paper proposed a non-invasive method in early screening of leukemia using NIRS. In this method NIRs is applied directly at human fingertip for spectral data acquisition and standard blood test procedure which involve blood draw is done for laboratory data acquisition. The prediction model will compared the spectral data with laboratory data for validation. The performance of PCR and PLSR prediction model is compared for the selection of model with high accuracy level. PLSR shows a better performance compared to PCR.