Artificial Intelligence (AI) is set to transform medical imaging by leveraging the vast data
contained in medical images. Deep learning and radiomics are the two main AI methods …

Purpose to evaluate the diagnostic performance of radiomics in lymph node metastasis
(LNM) prediction in patients with papillary thyroid carcinoma (PTC) through a systematic …

Purpose To propose a new quality scoring tool, METhodological RadiomICs Score
(METRICS), to assess and improve research quality of radiomics studies. Methods We …

Objectives To investigate the intra-and inter-rater reliability of the total radiomics quality
score (RQS) and the reproducibility of individual RQS items' score in a large multireader …

In the field of computer science, known as artificial intelligence, algorithms imitate reasoning
tasks that are typically performed by humans. The techniques that allow machines to learn …

Objectives To predict tumor grade (G1 vs. G2/3), presence of distant metastasis (M+),
metastatic lymph nodes (N+), and microvascular invasion (VI) of pancreatic neuroendocrine …

Hepatocellular carcinoma (HCC) remains not only a cause of a considerable part of
oncologic mortality, but also a diagnostic and therapeutic challenge for healthcare systems …

Simple Summary Given the variable aggressiveness of PCa, patients with indolent PCa do
not require intervention, but rather require active surveillance and close lifelong follow-up …

Assessment of the quality and current performance of computed tomography (CT) radiomics-
based models in predicting epidermal growth factor receptor (EGFR) mutation status in …

Background The new immunotherapies have not only changed the oncological therapeutic
approach but have also made it necessary to develop new imaging methods for assessing …