European Radiology

Machine learning based on the multimodal connectome can predict the preclinical stage of Alzheimer’s disease: a preliminary study

Subjective cognitive decline (SCD) may be a preclinical stage of Alzheimer’s disease (AD). For this preliminary study, the authors recruited one hundred...

European Radiology

2 weeks ago

Automated segmentation and quantification of the healthy and diseased aorta in CT angiographies using a dedicated deep learning approach

Performed between 2015 and 2018, the purpose of this study was to develop and validate a deep learning-based algorithm for the segmentation and quantification...

European Radiology

1 month ago

Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data

Although challenging to predict, early recognition of COVID-19 severity can help guide patient management. The authors of this study aimed to develop an...

European Radiology

1 month ago

Combined radiomics-clinical model to predict malignancy of vertebral compression fractures on CT

The authors of this study aimed to develop and validate a combined radiomics-clinical model to predict malignancy of cerebral compression fractures on CT....

European Radiology

2 months ago

A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients

The authors of this study analyzed and compared the imaging workflow, radiation dose, and image quality for 127 adult COVID-19 patients who were examined...

European Radiology

2 months ago

An A.I. classifier derived from 4D radiomics of dynamic contrast-enhanced breast MRI data: potential to avoid unnecessary breast biopsies

In this retrospective study, the authors aimed to evaluate a temporally and spatially resolved (4D) radiomics approach to distinguish benign from malignant...

European Radiology

3 months ago

Pneumothorax detection in chest radiographs: optimizing artificial intelligence system for accuracy and confounding bias reduction using in-image annotations in algorithm training

Due to the noisy annotation quality of public training data and confounding thoracic tubes, the diagnostic accuracy of artificial intelligence (AI)...

European Radiology

3 months ago

Development and multicenter validation of a CT-based radiomics signature for predicting severe COVID-19 pneumonia

The authors of this study aimed to develop and validate a radiomics nomogram for the prompt prediction of severe COVID-19 pneumonia. This was done through the...

European Radiology

3 months ago

Machine learning based on clinical characteristics and chest CT quantitative measurements for prediction of adverse clinical outcomes in hospitalized patients with COVID-19

In this study, the authors aimed to develop and validate a machine learning model for the prediction of adverse outcomes in hospitalized patients with...

European Radiology

4 months ago

Opportunistic osteoporosis screening in multi-detector CT images using deep convolutional neural networks

In this study, the authors explored the application of deep learning in patients with primary osteoporosis. Furthermore, they aimed to develop a fully...

European Radiology

4 months ago