Title :
Preliminary study on the quick detection of acquired immure deficiency syndrome by saliva analysis using surface enhanced Raman spectroscopic technique
Author :
Yan, Wang ; Lin, Hua ; Jinghua, Liu ; Dian, Qu ; Anyu, Chen ; Yi, Jiao ; Xun, Guo ; Chunwei, Liu ; Wen, Huang ; Hong, Wang
Author_Institution :
Biomed. Eng. Coll., Capital Univ. of Med. Sci., Beijing, China
Abstract :
45 saliva samples of AIDS patients and 55 saliva samples in normal population were detected by the Surface-enhanced Raman spectroscopy (SERS) system. And the spectrum data were analyzed using the Support Vector Machine (SVM) algorithm, one of the data mining technologies. Statistical analysis showed that two groups were distinguished effectively. This study provided a new research direction of the quick non-invasive testing for AIDS.
Keywords :
data mining; diseases; patient diagnosis; statistical analysis; support vector machines; surface enhanced Raman scattering; AIDS detection; acquired immure deficiency syndrome; data mining; saliva analysis; statistical analysis; support vector machine; surface enhanced Raman spectroscopy; Acquired Immunodeficiency Syndrome; Algorithms; Artificial Intelligence; Biological Markers; Diagnosis, Computer-Assisted; Humans; Pattern Recognition, Automated; Pilot Projects; Reproducibility of Results; Saliva; Sensitivity and Specificity; Spectrum Analysis, Raman;
Conference_Titel :
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4244-3296-7
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2009.5333131
