Purpose The aim of this study was to assess the potential of machine learning with
multiparametric magnetic resonance imaging (mpMRI) for the early prediction of …

Purpose To determine whether a multivariate machine learning-based model using
computer-extracted features of pre-treatment dynamic contrast-enhanced magnetic …

Objectives: To investigate the ability of radiomic signatures based on MRI to evaluate the
response and efficiency of neoadjuvant chemotherapy (NAC) for treating breast cancers …

Objectives The purpose of this study was to determine whether multiparametric magnetic
resonance imaging (MRI) using dynamic contrast-enhanced MRI (DCE-MRI) and diffusion …

Purpose: We evaluated the performance of the newly proposed radiomics of multiparametric
MRI (RMM), developed and validated based on a multicenter dataset adopting a radiomic …

Purpose To develop a new quantitative global kinetic breast magnetic resonance imaging
(MRI) features analysis scheme and assess its feasibility to assess tumor response to …

Purpose The aim of this meta-analysis was to determine the diagnostic accuracy of machine
learning (ML) models with MRI in predicting pathological response to neoadjuvant …

Objective To explore the predictive value of parameters derived from diffusion-weighted
imaging (DWI) and contrast-enhanced (CE)-MRI at different time-points during neoadjuvant …

In patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy
(NAC), some patients achieve a complete pathologic response (pCR), some achieve a …

Purpose To evaluate the value of multiparametric magnetic resonance imaging (MRI) in
pretreatment prediction of breast cancers insensitive to neoadjuvant chemotherapy (NAC) …