Radiomics is the method of choice for investigating the association between cancer imaging
phenotype, cancer genotype and clinical outcome prediction in the era of precision …

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

Osteoarthritis (OA) is one of the fast-growing disability-related diseases worldwide, which
has significantly affected the quality of patients' lives and brings about substantial …

The field of radiomics is at the forefront of personalized medicine. However, there is concern
that high variation in imaging parameters will impact robustness of radiomic features and …

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

Background Current imaging methods for prediction of complete margin resection (R0) in
patients with pancreatic ductal adenocarcinoma (PDAC) are not reliable. Purpose To …

Purpose The study aimed to predict acute radiation esophagitis (ARE) with grade≥ 2 for
patients with locally advanced lung cancer (LALC) treated with intensity-modulated radiation …

Radiomic model reliability is a central premise for its clinical translation. Presently, it is
assessed using test–retest or external data, which, unfortunately, is often scarce in reality …

Background and purpose Radiomics allows extraction of quantifiable features from imaging.
This study performs a systematic review and meta-analysis of the performance of radiomics …

Radiomics features extracted from medical images have been widely reported to be useful
in the patient specific outcome modeling for variety of assessment and prediction purposes …