Medical imaging can assess the tumor and its environment in their entirety, which makes it
suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in …

Purpose The aim of this systematic review was to analyse literature on artificial intelligence
(AI) and radiomics, including all medical imaging modalities, for oncological and non …

Background & Aims Microvascular invasion (MVI) impairs surgical outcomes in patients with
hepatocellular carcinoma (HCC). As there is no single highly reliable factor to preoperatively …

Purpose: We aimed to evaluate the value of deep learning on positron emission tomography
with computed tomography (PET/CT)–based radiomics for individual induction …

Background Intratumor heterogeneity in lung cancer may influence outcomes. CT radiomics
seeks to assess tumor features to provide detailed imaging features. However, CT radiomic …

Background: Radiomics has emerged as a new approach that can help identify imaging
information associated with tumor pathophysiology. We developed and validated a …

Purpose To investigate the feasibility of tumor type prediction with MRI radiomic image
features of different brain metastases in a multiclass machine learning approach for patients …

Objectives To develop and validate a radiomics nomogram for preoperative prediction of
microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC). Methods The …

Objectives To develop and validate a radiomics predictive model based on pre-treatment
multiparameter magnetic resonance imaging (MRI) features and clinical features to predict a …

Purpose: The purpose of this study is to develop and validate a nomogram model combing
radiomics features and clinical characteristics to preoperatively differentiate grade 1 and …