Subjective cognitive decline (SCD) may be a preclinical stage of Alzheimer’s disease (AD). For this preliminary study, the authors recruited one hundred...
In this article, the authors aimed to guide and inform the radiology community regarding key methodological aspects of machine learning (ML) in order to...
The purpose of this study was to classify the most common types of plain radiography through the use of a neural network and, subsequently, to validate the...
In recent years, artificial intelligence (AI) and, in particular, the application of machine learning (ML) algorithms, have become a new cornerstone in...
The purpose of this single-center retrospective study was to investigate the effectiveness of contrast-enhanced computed tomography (CECT)-based radiomic...
This retrospective study aimed to investigate whether radiomics features extracted from MRI of BRCA-positive patients with sub-centimeter breast masses can be...
The authors of this retrospective study aimed to develop and validate a CT-based radiomics model for preoperative prediction of spread through air space...
In this study, the authors aimed to evaluate whether MRI-based radiomic features were able to improve the accuracy of survival predictions for lower grade...
New machine learning techniques, especially deep neural networks, hold the promise of revolutionizing many aspects of radiology and have gained immense public...
The goal of this study was to assess the diagnostic accuracy of machine learning in the prediction of isocitrate dehydrogenase (IDH) mutations, particularly...
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.