Radiomics-based Prognosis Analysis for Non-Small Cell Lung Cancer
Abstract
Radiomics characterizes tumor phenotypes by extracting large numbers of quantitative features from radiological images. Radiomic features have been shown to provide prognostic value in predicting clinical outcomes in several studies. However, several challenges including feature redundancy, unbalanced data, and small sample sizes have led to relatively low predictive accuracy. In this study, we explore different strategies for overcoming these...
Paper Details
Title
Radiomics-based Prognosis Analysis for Non-Small Cell Lung Cancer
Published Date
Apr 18, 2017
Journal
Volume
7
Issue
1
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