radiomics

Dual-energy CT–based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer

In this study, the authors aimed to build a dual-energy CT (DECT)-based deep learning radiomics nomogram that could be used for lymph node metastasis...

European Radiology

2 weeks ago

Radiogenomics of lower-grade gliomas: machine learning–based MRI texture analysis for predicting 1p/19q codeletion status

In this work, we aimed to evaluate the potential value of the machine learning (ML)–based MRI texture analysis for predicting 1p/19q codeletion status of...

Burak Kocak

2 months ago

Combining DWI radiomics features with transurethral resection promotes the differentiation between muscle-invasive bladder cancer and non-muscle-invasive bladder cancer

The purpose of this retrospective study was to investigate the value of radiomics features from diffusion-weighted imaging (DWI) in differentiating...

European Radiology

3 months ago

A machine learning model for the prediction of survival and tumor subtype in pancreatic ductal adenocarcinoma from preoperative diffusion-weighted imaging

The aim of this study was to develop a supervised machine learning (ML) algorithm that would use diffusion-weighted imaging-derived radiomic features to...

European Radiology Experimental

5 months ago

MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma

This study integrated the clinical data and radiomics signature generated by a support vector machine to establish a radiomics nomogram for prediction of...

European Radiology

5 months ago

Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation

The goal of this study was to measure the reproducibility of radiomic features in pancreatic parenchyma and ductal adenocarcinomas in patients who underwent...

Richard Do

6 months ago

Radiomics machine-learning signature for diagnosis of hepatocellular carcinoma in cirrhotic patients with indeterminate liver nodules

This article sets out to determine whether machine learning can be used to train and calibrate the signature for diagnosing hepatocellular carcinoma in...

European Radiology

6 months ago

Breast cancer Ki-67 expression prediction by digital breast tomosynthesis radiomics features

Despite the encouraging results, more studies are needed in order to further evaluate these preliminary findings and to find to what extent radiomics and AI...

Alberto Tagliafico

7 months ago

Why radiomics research does not translate to clinical practice: evaluation of literature using RQS and TRIPOD

Over the last few years, the number of studies published using quantitative imaging biomarkers to classify or predict pathologies has steadily increased. As...

Daniel Pinto dos Santos

8 months ago

MRI radiomics in categorizing ovarian masses and predicting clinical outcome: a preliminary study

This study aimed to assess whether MRI radiomics can categorize ovarian masses and to determine the association between MRI radiomics and survival among...

European Radiology

10 months ago