Decision Support for Breast Cancer Detection: Classification Improvement Through Feature Selection.

ABSTRACT: Several statistical-based approaches have been developed to support medical personnel in early breast cancer detection. This article presents a method for feature selection aimed at classifying cases into categories based on patients' breast tissue measures and protein microarray. The effectiveness of this feature selection strategy was evaluated against the commonly used Wisconsin Breast Cancer Database-WBCD (with several patients and fewer features) and a new protein microarray data set (with several features and fewer patients). Features were ranked according to a feature importance index that combines parameters emerging from the unsupervised method of principal component analysis and the supervised method of Bhattacharyya distance. Observations of a training set were iteratively categ

SUBMITTER: Fogliatto FS 

PROVIDER: S-EPMC6755645 | biostudies-literature | 2019 Jan-Dec

REPOSITORIES: biostudies-literature