An important challenge in the use of artificial intelligence (AI) for medical image segmentation tasks is the lack of high-quality, scan protocol-specific...
This retrospective, multi-institutional study investigated machine learning classifiers and interpretable models using chest CT for the detection of COVID-19...
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...
In this study, the authors aimed to develop and validate a machine learning model for the prediction of adverse outcomes in hospitalized patients with...
This study used a sample of 131 participants who underwent low-dose computed tomography (LDCT) and standard-dose computed tomography (SDCT) to determine the...
In this study, the authors proposed a deep learning method for the detection and quantification of pneumothorax in heterogeneous routine clinical data, which...
Decisions regarding the optimal management of unruptured intracranial aneurysms (UIAs) depend on a comprehensive comparison of the risks between aneurysm...
The aim of this study was to evaluate whether machine learning algorithms allow for the prediction of Child-Pugh classification on clinical multiphase...
Among solid tumors, testicular germ cell tumors (TGCT) are the most common entity in men below the age of 40, and they are very likely to metastasize. The...
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...
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.
