Embedding filtering criteria into a wrapper marker selection method for brain tumor classification: An application on metabolic peak area ratios
| Autor: | Geert Postma, X. Kotsiakis, George C. Giakos, M. Zervakis, M.G. Kounelakis, Lutgarde M. C. Buydens |
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| Rok vydání: | 2011 |
| Předmět: |
Peak area
Biomedical Computer science business.industry Applied Mathematics Brain tumor Pattern recognition Feature selection computer.software_genre medicine.disease Ranking (information retrieval) Analytical Chemistry Set (abstract data type) Clinical diagnosis medicine Embedding Data mining Artificial intelligence business Marker selection Instrumentation Engineering (miscellaneous) computer |
| Zdroj: | Measurement Science & Technology, 22, 11 Measurement Science & Technology, 22 |
| ISSN: | 0957-0233 |
| Popis: | Summarization: The purpose of this study is to identify reliable sets of metabolic markers that provide accurate classification of complex brain tumors and facilitate the process of clinical diagnosis. Several ratios of metabolites are tested alone or in combination with imaging markers. A wrapper feature selection and classification methodology is studied, employing Fisher's criterion for ranking the markers. The set of extracted markers that express statistical significance is further studied in terms of biological behavior with respect to the brain tumor type and grade. The outcome of this study indicates that the proposed method by exploiting the intrinsic properties of data can actually reveal reliable and biologically relevant sets of metabolic markers, which form an important adjunct toward a more accurate type and grade discrimination of complex brain tumors Παρουσιάστηκε στο: Measurement Science and Technology |
| Databáze: | OpenAIRE |
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