| Autor: |
Assareh A; Biomedical Engineering Faculty of Amirkabir University of Technology, Tehran, Iran., Moradi MH, Esmaeili V |
| Jazyk: |
angličtina |
| Zdroj: |
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2007; Vol. 2007, pp. 5988-91. |
| DOI: |
10.1109/IEMBS.2007.4353712 |
| Abstrakt: |
Protein mass spectra pattern recognition is a new forum in which many machine learning algorithms have been conducted to enhance the chance of early cancer diagnosis. The high-dimensionality-small-sample (HDSS) problem of cancer proteomic datasets still requires more sophisticated approaches to improve the classification accuracy. In this study we present a simple ensemble strategy based on measuring the generalizing capability of different subsets of training data and apply it in making final decision. Using a limited number of biomarkers along with 5 classification algorithms, the proposed method achieved a promising performance over a well-known prostate cancer mass spectroscopy dataset. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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