Publications

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

1 month 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

1 month ago

Radiomics approach for survival prediction in chronic obstructive pulmonary disease

The idea of quantification of disease severity of chronic obstructive pulmonary disease (COPD) with CT has been introduced as early as the late 1980s with the...

Joon Beom Seo

2 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

2 months ago

Radiology artificial intelligence, a systematic evaluation of methods (RAISE): a systematic review protocol

The review was prospectively registered on PROSPERO and adheres to the PRISMA protocols. We decided to undertake the systematic review because while there is...

Brendan Kelly

2 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

2 months ago

How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts

In this article, the authors aimed to guide and inform the radiology community regarding key methodological aspects of machine learning (ML) in order to...

European Radiology

3 months ago

Diagnostic performance for pulmonary adenocarcinoma on CT: comparison of radiologists with and without three-dimensional convolutional neural network

Convolutional neural networks (CNNs) are often used in the area of image recognition. We constructed the three dimensional (3D)-CNN model to predict pulmonary...

Masahiro Yanagawa

3 months ago

To buy or not to buy—evaluating commercial AI solutions in radiology (the ECLAIR guidelines)

Artificial intelligence (AI) has certainly made impressive progress over the past few years. Consequently, many companies have entered the market bombarding...

Patrick Omoumi & Daniel Pinto dos Santos

3 months ago

Development of MR-based preoperative nomograms predicting DNA copy number subtype in lower grade gliomas with prognostic implication

The aim of this study was to determine the value of MR-based preoperative nomograms in predicting DNA copy number (CN) subtype in patients with lower grade...

European Radiology

3 months ago