Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male
population. The diagnosis, the identification of aggressive disease, and the post-treatment …

Radiomics and genomics represent two of the most promising fields of cancer research,
designed to improve the risk stratification and disease management of patients with prostate …

Background Prediction of microvascular invasion (MVI) may help determine treatment
strategies for hepatocellular carcinoma (HCC). Purpose To develop a radiomics approach …

Background Many studies in radiomics are using feature selection methods to identify the
most predictive features. At the same time, they employ cross-validation to estimate the …

Purpose The hypoxic microenvironment is involved in the tumorigenesis of ovarian cancer
(OC). Therefore, we aim to develop a non-invasive radiogenomics approach to identify a …

Radiomics aims to support clinical decisions through its workflow, which is divided into:(i)
target identification and segmentation,(ii) feature extraction,(iii) feature selection, and (iv) …

Objectives A critical problem in radiomic studies is the high dimensionality of the datasets,
which stems from small sample sizes and many generic features extracted from the volume …

Purpose To establish radiomics prediction models based on automatic segmented magnetic
resonance imaging (MRI) for predicting the systemic recurrence of triple-negative breast …

Background Noninvasive detection of TP53 mutations is useful for the molecular
stratification of breast cancer. Purpose To explore MRI radiomics features reflecting TP53 …

Background In radiomic studies, several models are often trained with different combinations
of feature selection methods and classifiers. The features of the best model are usually …