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 …

Colorectal cancer (CRC) is the third most common malignancy worldwide, with
approximately 50% of patients develo** colorectal cancer liver metastasis (CRLM) during …

Background Macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is
an aggressive variant associated with angiogenesis and immunosuppressive tumor …

Purpose: Using standard-of-care CT images obtained from patients with a diagnosis of non–
small cell lung cancer (NSCLC), we defined radiomics signatures predicting the sensitivity of …

Objectives Radiomic features derived from routine medical images show great potential for
personalized medicine in gastric cancer (GC). We aimed to evaluate the current status and …

In current clinical practice, tumor response assessment is usually based on tumor size
change on serial computerized tomography (CT) scan images. However, evaluation of tumor …

Rapid advances in automated methods for extracting large numbers of quantitative features
from medical images have led to tremendous growth of publications reporting on radiomic …

Purpose To assess the efficacy of radiomics features obtained by T2-weighted sequences to
predict clinical outcomes following liver resection in colorectal liver metastases patients …

Importance Existing criteria to estimate the benefit of a therapy in patients with cancer rely
almost exclusively on tumor size, an approach that was not designed to estimate survival …

Purpose The purpose of this study is to evaluate the Radiomics and Machine Learning
Analysis based on MRI in the assessment of Liver Mucinous Colorectal Metastases. Query …