Radiomics is the quantitative analysis of standard‐of‑care medical imaging; the information
obtained can be applied within clinical decision support systems to create diagnostic …

Modern medicine is reliant on various medical imaging technologies for non-invasively
observing patients' anatomy. However, the interpretation of medical images can be highly …

Background Numerous features are commonly generated in radiomics applications as
applied to medical imaging, and identification of robust radiomics features (RFs) can be an …

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 …

Radiomics research is rapidly growing in recent years, but more concerns on radiomics
reliability are also raised. This review attempts to update and overview the current status of …

Foundation models in deep learning are characterized by a single large-scale model trained
on vast amounts of data serving as the foundation for various downstream tasks. Foundation …

Radiomics is a high-throughput approach to image phenotyping. It uses computer
algorithms to extract and analyze a large number of quantitative features from radiological …

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

Radiomics is a technique that extracts quantitative features from medical images using data‐
characterization algorithms. Radiomic features can be used to identify tissue characteristics …

Abstract Background and Purpose Although quantitative image biomarkers (radiomics)
show promising value for cancer diagnosis, prognosis, and treatment assessment, these …