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
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;
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
DOI :
10.1109/IEMBS.2005.1615880
