Purpose Advanced medical image analytics is increasingly used to predict clinical outcome
in patients diagnosed with gastrointestinal tumors. This review provides an overview on the …

Background and purpose Robust parameters are needed to predict lymph node metastasis
(LNM) in locally advanced cervical cancer patients in order to select optimal treatment …

Purpose Our study investigated the contribution that the application of radiomics analysis on
post-treatment magnetic resonance imaging can add to the assessments performed by an …

Objectives To date, radiomics has been applied in oncology for over a decade and has
shown great progress. We used a bibliometric analysis to analyze the publications of …

Objective The aim of this study was to investigate whether pretherapeutic, multiparametric
magnetic resonance imaging (MRI) radiomic features can be used for predicting non …

Purpose To predict the neoadjuvant chemoradiation therapy (CRT) response in patients with
locally advanced rectal cancer (LARC) using radiomics and deep learning based on pre …

Radiomics analyses commonly apply imaging features of different complexity for the
prediction of the endpoint of interest. However, the prognostic value of each feature class is …

Purpose Aim of this study was to develop a generalised radiomics model for predicting
pathological complete response after neoadjuvant chemo-radiotherapy in locally advanced …

Purpose To establish and validate a radiomics model based on multi-sequence magnetic
resonance (MR) images for preoperative prediction of immunoscore in rectal cancer …

Purpose Radiomics are a set of methods used to leverage medical imaging and extract
quantitative features that can characterize a patient's phenotype. All modalities can be used …