Name
Title | ||
|---|---|---|
Cost-Sensitive Classification on Pathogen Species of Bacterial Meningitis by Surface Enhanced Raman Scattering |
Abstract | ||
|---|---|---|
We propose a pathogen-classification system using the Surface-Enhanced Raman Scattering (SERS) platform. The system differentiates the pathogens based on their SERS spectra, which are believed to be related to the surface chemical components. The specialty of the system is to not only consider the usual classification accuracy, but also pay attention to the different types of costs during misclassification. For instance, due to the effectiveness of treatments, the cost of classifying a Gram-positive bacterium as another Gram-positive one should be lower than the cost of classifying a Gram-positive bacterium as a Gram-negative one. We express the task as the cost-sensitiveclassification problem, and take state-of-the-art cost-sensitiveclassification algorithms from the machine learning community to conquer the task. Our experimental study validates the usefulness of those algorithms on building the system. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/BIBM.2011.133 | BIBM |
Keywords | Field | DocType |
state-of-the-art cost-sensitiveclassification algorithm,bacterial meningitis,usual classification accuracy,experimental study,surface chemical component,surface-enhanced raman scattering,different type,cost-sensitive classification,cost-sensitiveclassification problem,gram-positive bacterium,surface enhanced raman scattering,sers spectrum,pathogen species,pathogen-classification system,raman spectra,microorganisms,svm,classification system,machine learning,learning artificial intelligence | Computer science,Support vector machine,Raman scattering,Artificial intelligence,Bioinformatics,Machine learning | Conference |
ISSN | Citations | PageRank |
2156-1125 | 2 | 0.38 |
References | Authors | |
7 | 15 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Te-Kang Jan | 1 | 12 | 1.28 |
| Hsuan-Tien Lin | 2 | 829 | 74.77 |
| Hsin-Pai Chen | 3 | 2 | 0.38 |
| Tsung-Chen Chern | 4 | 2 | 0.38 |
| Chung-Yueh Huang | 5 | 4 | 0.79 |
| Bing-Cheng Wen | 6 | 4 | 0.79 |
| Chia-Wen Chung | 7 | 4 | 0.79 |
| Yung-Jui Li | 8 | 4 | 0.79 |
| Ya-Ching Chuang | 9 | 4 | 0.79 |
| Li-Li Li | 10 | 4 | 0.79 |
| Yu-Jiun Chan | 11 | 2 | 0.38 |
| Juen-Kai Wang | 12 | 5 | 1.54 |
| Yuh-Lin Wang | 13 | 5 | 1.54 |
| Chi-Hung Lin | 14 | 217 | 34.67 |
| Da-Wei Wang | 15 | 39 | 5.93 |