TY - GEN
T1 - Hybrid SVM/CART classification of pathogenic species of bacterial meningitis with surface-enhanced raman scattering
AU - Huang, Chung Yueh
AU - Tsai, Tsung Heng
AU - Wen, Bing Cheng
AU - Chung, Chia Wen
AU - Li, Yung Jui
AU - Chuang, Ya Ching
AU - Lin, Wen Jie
AU - Li, Li Li
AU - Wang, Juen Kai
AU - Wang, Yuh Lin
AU - Lin, Chi Hung
AU - Wang, Da Wei
PY - 2010
Y1 - 2010
N2 - Bacterial meningitis is still a life-threatening disease, and early diagnosis of pathogen can be crucial to improving survival rate. Using the surface-enhanced Raman scattering (SERS) platform developed by our group, the pathogens can be differentiated on the basis of their SERS spectra which are believed to related to their surface chemical components. We collected the SERS spectra of ten pathogens: Streptococcus pneumoniae(Spn), Streptococcus agalactiae (group B streptococcus, GBS), Staphylococcus aureus (Sa), Pseudomonas aeruginosae (Psa), Acinetobacter baumannii (Ab), Klebsiella pneumoniae (Kp), Neisseria meningitidis (Nm), Listeria monocytogenes (Lm), Haemophilus influenzae (Hi), and Escherichia coli (E.coli). These samples were obtained from patients in National Taiwan University Hospital, and were believed to represent the real diversity of clinical pathogens. Using the support vector machine (SVM) method, the classification accuracy can achieve around 88%. However, we noted that SVM cannot distinguish between [E.coli, Kp] and [Sa, Hi] due to the fact that the global features of these two groups of pathogens are very similar. We therefore incorporated a classification tree method that can focus on local differences in classification rules. This improved the accuracy to 90%. To get a better understanding of the SERS signals, we also compared several other classification methods. In addition, rule extraction method which attempts to explain why classifier fail or succeed is also discussed. Our preliminary results are interesting, encouraging, and await more thorough investigation.
AB - Bacterial meningitis is still a life-threatening disease, and early diagnosis of pathogen can be crucial to improving survival rate. Using the surface-enhanced Raman scattering (SERS) platform developed by our group, the pathogens can be differentiated on the basis of their SERS spectra which are believed to related to their surface chemical components. We collected the SERS spectra of ten pathogens: Streptococcus pneumoniae(Spn), Streptococcus agalactiae (group B streptococcus, GBS), Staphylococcus aureus (Sa), Pseudomonas aeruginosae (Psa), Acinetobacter baumannii (Ab), Klebsiella pneumoniae (Kp), Neisseria meningitidis (Nm), Listeria monocytogenes (Lm), Haemophilus influenzae (Hi), and Escherichia coli (E.coli). These samples were obtained from patients in National Taiwan University Hospital, and were believed to represent the real diversity of clinical pathogens. Using the support vector machine (SVM) method, the classification accuracy can achieve around 88%. However, we noted that SVM cannot distinguish between [E.coli, Kp] and [Sa, Hi] due to the fact that the global features of these two groups of pathogens are very similar. We therefore incorporated a classification tree method that can focus on local differences in classification rules. This improved the accuracy to 90%. To get a better understanding of the SERS signals, we also compared several other classification methods. In addition, rule extraction method which attempts to explain why classifier fail or succeed is also discussed. Our preliminary results are interesting, encouraging, and await more thorough investigation.
KW - CART
KW - Hybrid SVM
KW - SERS
KW - SVM
UR - http://www.scopus.com/inward/record.url?scp=79952432469&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952432469&partnerID=8YFLogxK
U2 - 10.1109/BIBM.2010.5706600
DO - 10.1109/BIBM.2010.5706600
M3 - Conference contribution
AN - SCOPUS:79952432469
SN - 9781424483075
T3 - Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
SP - 406
EP - 409
BT - Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
T2 - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
Y2 - 18 December 2010 through 21 December 2010
ER -