Prediction of pathologic complete response to neoadjuvant systemic therapy in triple negative breast cancer using deep learning on multiparametric MRIZijian Zhou, Jingfei Ma, Zhan Xu et al.|Scientific Reports|2023Cited by 44
A Radiomics Model Based on Synthetic MRI Acquisition for Predicting Neoadjuvant Systemic Treatment Response in Triple-Negative Breast CancerKen‐Pin Hwang, Gaiane M. Rauch, Nabil Elshafeey et al.|Radiology Imaging Cancer|2023Cited by 32
Assessment of Response to Neoadjuvant Systemic Treatment in Triple-Negative Breast Cancer Using Functional Tumor Volumes from Longitudinal Dynamic Contrast-Enhanced MRIBikash Panthi, Gaiane M. Rauch, Beatriz E. Adrada et al.|Cancers|2023Cited by 25
Deep Learning for Fully Automatic Tumor Segmentation on Serially Acquired Dynamic Contrast-Enhanced MRI Images of Triple-Negative Breast CancerZhan Xu, Jingfei Ma, David E Rauch et al.|Cancers|2023Cited by 9