The authors of this retrospective study had the goal of evaluating the effectiveness of radiomics signatures in order to predict the tumor response of...
The aim of this study was to compare the performance of a deep learning (DL)-based method used for diagnosing pulmonary nodules compared with the diagnostic...
The purpose of this study was to evaluate the performance of deep learning using ResNet50 in the differentiation of benign and malignant vertebral fracture on...
As a junior radiology trainee, when I was not in the reporting room or on the wards doing portable ultrasounds, I found learning CT procedures a daunting task...
Of late, deep learning-based algorithms have been successfully applied to various medical imaging modalities, ranging from chest radiographs to head CT scans....
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...
In this study, the authors explored the application of deep learning in patients with primary osteoporosis. Furthermore, they aimed to develop a fully...
The authors of this study aimed to evaluate the image quality of low iodine concentration, dual-energy CT (DECT) combined with a deep learning-based noise...
Welcome to the blog on Artificial Intelligence of the European Society of Radiology
This blog aims at bringing educational and critical perspectives on AI to readers. It should help imaging professionals to learn and keep up to date with the technologies being developed in this rapidly evolving field.