Conference proceeding
Creating Prognostic Systems by the Mann-Whitney Parameter
2018 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), pp 33-39
Sep 2018
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
We proposed two approaches to compute Mann-Whitney parameter based initial dissimilarities for the Ensemble Algorithm for Clustering Cancer Data (EACCD). These two approaches are non-parametric and produce robust prognostic systems. The breast cancer data from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute were used to demonstrate these two approaches. Results showed that our proposed methods generated prognostic systems with a comparable performance to the AJCC's cancer staging system.
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Details
- Title
- Creating Prognostic Systems by the Mann-Whitney Parameter
- Creators
- Huan Wang - George Washington UniversityMatthew Hueman - Walter Reed National Military Medical CenterQing Pan - George Washington UniversityDonald Henson - Uniformed Services University of the Health SciencesArnold Schwartz - George Washington UniversityLi Sheng - Drexel UniversityDechang Chen - Uniformed Services University of the Health SciencesIEEE
- Publication Details
- 2018 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), pp 33-39
- Publisher
- Association for Computing Machinery (ACM)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Mathematics
- Web of Science ID
- WOS:000466953000016
- Scopus ID
- 2-s2.0-85063251702
- Other Identifier
- 991019168125204721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Engineering, Biomedical
- Medical Informatics