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 …

Simple Summary Radiomics could increase the value of medical images for oncologic
patients, allowing for the identification of novel imaging biomarkers and building prediction …

Feature selection is an important preprocessing technology for dimensionality reduction,
which reduces the dimension of the dataset by acquiring a subset of features with the largest …

The use of artificial intelligence (AI) with medical images to solve clinical problems is
becoming increasingly common, and the development of new AI solutions is leading to more …

Artificial intelligence (AI) and machine learning (ML) are increasingly used in radiology
research to deal with large and complex imaging data sets. Nowadays, ML tools have …

A simple PubMed search using the term “radiomics” on February 28, 2023, reveals 7857
publications at the time of the writing, with no time filter applied. Despite this level of …

Diabetic retinopathy (DR), a common ocular microvascular complication of diabetes,
contributes significantly to diabetes-related vision loss. This study addresses the imperative …

Background Application of radiomics proceeds by extracting and analysing imaging features
based on generic morphological, textural, and statistical features defined by formulas …

Objectives To evaluate the performance of machine learning–augmented MRI-based
radiomics models for predicting response to neoadjuvant chemotherapy (NAC) in soft tissue …

Objectives In radiomics, different feature normalization methods, such as z-Score or Min–
Max, are currently utilized, but their specific impact on the model is unclear. We aimed to …