Personalized treatment strategies for cancer frequently rely on the detection of genetic
alterations which are determined by molecular biology assays. Historically, these processes …

The main therapeutic options for colorectal cancer are surgical resection and adjuvant
chemotherapy in non-metastatic disease. However, the evaluation of the overall adjuvant …

Objective The aim of this study was the evaluation radiomics analysis efficacy performed
using computed tomography (CT) and magnetic resonance imaging in the prediction of …

Background: breast cancer (BC) is the world's most prevalent cancer in the female
population, with 2.3 million new cases diagnosed worldwide in 2020. The great efforts made …

Objectives Machine learning (ML) for medical imaging is emerging for several organs and
image modalities. Our objectives were to provide clinicians with an overview of this field by …

Background: This paper offers an assessment of radiomics tools in the evaluation of
intrahepatic cholangiocarcinoma. Methods: The PubMed database was searched for papers …

Computed tomography (CT) introduced medicine to digital imaging. This occurred in the
early 1970s and it was the start of the digital medical imaging revolution. The resulting …

In the realm of managing malignant liver tumors, the convergence of radiomics and machine
learning has redefined the landscape of medical practice. The field of radiomics employs …

In patients with colorectal liver metastasis (CRLMs) unsuitable for surgery, oncological
treatments, such as chemotherapy and targeted agents, can be performed. Cross-sectional …

In this narrative review, we reported un up-to-date on the role of radiomics to assess
prognostic features, which can impact on the liver metastases patient treatment choice. In …