Due to the life-threatening nature of chronic pulmonary embolism (CPE) and how easily it can be misdiagnosed on computed tomography, the authors of this study...
The authors of this study used an artificial intelligence-based model in order to predict fragility fractures in postmenopausal women. Through a sample of 174...
In this study, the authors developed a fully automated artificial intelligence (AI)-based image analysis tool for segmenting skeletal muscle of the torso and...
The authors of this study aimed to determine the efficacy of a convolutional neural network (CNN) in final infarct volume prediction from computed tomography...
In this study, the authors proposed a deep learning method for the detection and quantification of pneumothorax in heterogeneous routine clinical data, which...
The aim of this study was to evaluate whether machine learning algorithms allow for the prediction of Child-Pugh classification on clinical multiphase...
This preliminary study aimed to differentiate malignant from benign enhancing foci on breast MRI using radiomic signature. Forty-five patients were included...
In this study, the authors aimed to determine whether features derived from texture analysis (TA) are able to distinguish between normal, benign, and...
The authors of this study aimed to assess the performance of a convolutional neural network (CNN) algorithm to register cross-sectional liver imaging series...
The aim of this study was to develop a supervised machine learning (ML) algorithm that would use diffusion-weighted imaging-derived radiomic features to...
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.