Radiomic Feature Selection Using Gradient Loss of Deep Neural Network for Lung Cancer Stage Detection 事件

Radiomic Feature Selection Using Gradient Loss of Deep Neural Network for Lung Cancer Stage Detection arXiv:2606.04453v1 Announce Type: new Abstract: Radiomics enables extraction of quantitative imaging biomarkers from medical images and has become an important tool for computer-aided cancer diagnosis. However, radiomics datasets are typically high-dimensional with limited samples, making feature selection a critical step for building reliable predictive models. This study proposes a Gradient-L