Meeting Banner
Abstract #3281

Use scout models for effective dimension reduction and feature selection in radiomics study

Yibo Dan1, Hongyue Tao2, Yida Wang1, Chengxiu Zhang1, Chenglong Wang1, Shuang Chen2, and Guang Yang1
1Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, shanghai, China, 2Department of Radiology, Huashan Hospital, Fudan University, shanghai, China

Radiomics has been used widely in image-based diagnosis and prognosis. Since radiomics studies often involve a small number of samples, effective dimension reduction and feature selection are crucial to the successful modeling. In this study, we proposed a heuristic method for effective dimension reduction and feature selection, which built a scout model for each category of features to select features from the category for the final model building. The approach was applied to the modeling with two different datasets, including the BraTS 2019 open data, and achieved results better than those of traditional methods on both datasets.

This abstract and the presentation materials are available to members only; a login is required.

Join Here