The high-throughput extraction of quantitative imaging features from medical images for the
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly developing and …

Objective The main aim of the present systematic review was a comprehensive overview of
the Radiomics Quality Score (RQS)–based systematic reviews to highlight common issues …

Magnetic resonance imaging (MRI) has gained increasing importance in the management of
rectal cancer over the last two decades. The role of MRI in patients with rectal cancer has …

Objectives Radiomic features derived from routine medical images show great potential for
personalized medicine in gastric cancer (GC). We aimed to evaluate the current status and …

Radiomics is a promising and fast-developing field within oncology that involves the mining
of quantitative high-dimensional data from medical images. Radiomics has the potential to …

Simple Summary Worldwide gastrointestinal (GI) malignancies account for about 25% of the
global cancer incidence. For some malignancies, screening programs, such as routine colon …

Background To develop and validate a survival model with clinico-biological features and
18F-FDG PET/CT radiomic features via machine learning, and for predicting the prognosis …

Artificial Intelligence (AI) is a branch of computer science that utilizes optimization,
probabilistic and statistical approaches to analyze and make predictions based on a vast …

The evaluation of the efficacy of different therapies is of paramount importance for the
patients and the clinicians in oncology, and it is usually possible by performing imaging …

While cross-sectional imaging has seen continuous progress and plays an undiscussed
pivotal role in the diagnostic management and treatment planning of patients with rectal …