Computer-extracted tumour characteristics have been incorporated into medical imaging
computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an …

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 …

The use of artificial intelligence (AI) and radiomics in the healthcare setting to advance
disease diagnosis and management and facilitate the creation of new therapeutics is …

Lung cancer is the leading cause of cancer-related deaths worldwide. It exhibits, at the
mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human …

Purpose To assess the efficacy of radiomics features obtained by T2-weighted sequences to
predict clinical outcomes following liver resection in colorectal liver metastases patients …

Radiomics is a rapidly developing field of research focused on the extraction of quantitative
features from medical images, thus converting these digital images into minable, high …

Purpose The purpose of this study is to evaluate the Radiomics and Machine Learning
Analysis based on MRI in the assessment of Liver Mucinous Colorectal Metastases. Query …

Simple Summary The two most common cross-sectional imaging modalities, computed
tomography (CT) and magnetic resonance imaging (MRI), have shown enormous utility in …

Simple Summary Lung cancer is a widespread malignant tumour with a high mortality and
morbidity rate and is frequently diagnosed in the middle and late stages when few therapies …

Background Radiomics and radiogenomics are two words that recur often in language of
radiologists, nuclear doctors and medical physicists especially in oncology field. Radiomics …