Conference proceeding
Analysis of an Ensemble Algorithm for Clustering Cancer Data
2012 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE WORKSHOPS (BIBMW), pp 754-755
01 Jan 2012
Abstract
In this paper, we present an analysis of the ensemble algorithm of clustering of cancer data (EACCD) by Chen et al. Using a breast cancer dataset, we demonstrate the effectiveness of EACCD in capturing differences among survival curves. We also investigate the impact of different settings in EACCD and compare EACCD with several other clustering approaches.
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4 citations in Scopus
Details
- Title
- Analysis of an Ensemble Algorithm for Clustering Cancer Data
- Creators
- Dengyuan Wu - George Washington Univ, Dept Comp Sci, Washington, DC 20052 USALi Sheng - Drexel University, MathematicsEric Xu - Univ Virginia, Dept Biol, Charlottesville, VA 22904 USAKai Xing - Univ Sci & Technol China, Dept Comp Sci, Beijing, Peoples R ChinaDechang Chen - Uniformed Serv Univ Hlth Sci, Div Epidemiol & Biostat, Bethesda, MD 20814 USA
- Publication Details
- 2012 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE WORKSHOPS (BIBMW), pp 754-755
- Series
- IEEE International Conference on Bioinformatics and Biomedicine Workshop-BIBMW
- Publisher
- IEEE
- Number of pages
- 2
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Mathematics
- Web of Science ID
- WOS:000320379600131
- Scopus ID
- 2-s2.0-84875603536
- Other Identifier
- 991019170359104721
InCites Highlights
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Mathematical & Computational Biology
- Medical Informatics