DocumentCode
1586159
Title
Diagnosis of breast cancer using HPLC metabonomics fingerprints coupled with computational methods
Author
Xiaohui Fan ; Jingqing Ba ; Peng Shen
Author_Institution
Pharm. Informatics Inst., Zhejiang Univ., Hangzhou
fYear
2006
Firstpage
6081
Lastpage
6084
Abstract
The present study was focused on developing a computational procedure for analysis of the HPLC metabonomics fingerprints of human urine to distinguish between patients with breast cancer from healthy people. The predictive rate of support vector machine (SVM) based diagnosis model is 100% for training set and 93.2% for test set, respectively. Current work might have important reference values to explore the methodology of metabonomics
Keywords
biochemistry; biological organs; cancer; chromatography; gynaecology; medical diagnostic computing; molecular biophysics; patient diagnosis; support vector machines; HPLC metabonomics fingerprints; breast cancer diagnosis; human urine; support vector machine; Breast cancer; Diseases; Educational institutions; Fingerprint recognition; Hospitals; Humans; Medical diagnostic imaging; Principal component analysis; Spectroscopy; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location
Shanghai
Print_ISBN
0-7803-8741-4
Type
conf
DOI
10.1109/IEMBS.2005.1615880
Filename
1615880
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