Radiomics is a quantitative approach to medical imaging, which aims at enhancing the
existing data available to clinicians by means of advanced mathematical analysis. Through …

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 …

Objectives To evaluate the utility of CT-based radiomics signatures in discriminating low-
grade (grades 1–2) clear cell renal cell carcinomas (ccRCC) from high-grade (grades 3–4) …

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

Purpose To investigate the performance of CT radiomics in predicting the overall survival
(OS) of patients with stage III clear cell renal carcinoma (ccRCC) after radical nephrectomy …

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 …

AIM To investigate machine learning based models combining clinical, radiomic, and
molecular information to distinguish between early true progression (tPD) and …

Background Advanced low rectal cancer has a non-negligible risk of lateral pelvic lymph
node (LPLN) metastasis (LPLNM) and lateral local recurrence (LR) after neoadjuvant …

Background This study aims to identify robust radiomic features for Magnetic Resonance
Imaging (MRI), assess feature selection and machine learning methods for overall survival …

This study aimed to introduce an alternative, inexpensive, and straightforward polymer with
specific mechanical and dielectric properties suitable for the fabrication of a clinical-grade …