machine learning

Machine learning based on the multimodal connectome can predict the preclinical stage of Alzheimer’s disease: a preliminary study

Subjective cognitive decline (SCD) may be a preclinical stage of Alzheimer’s disease (AD). For this preliminary study, the authors recruited one hundred...

European Radiology

2 years 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

2 years ago

Practical applications of deep learning: classifying the most common categories of plain radiographs in a PACS using a neural network

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...

European Radiology

2 years ago

Improved long-term prognostic value of coronary CT angiography-derived plaque measures and clinical parameters on adverse cardiac outcome using machine learning

In recent years, artificial intelligence (AI) and, in particular, the application of machine learning (ML) algorithms, have become a new cornerstone in...

Christian Tesche

2 years ago

Preoperative prediction for pathological grade of hepatocellular carcinoma via machine learning–based radiomics

The purpose of this single-center retrospective study was to investigate the effectiveness of contrast-enhanced computed tomography (CECT)-based radiomic...

European Radiology

2 years ago

Improved characterization of sub-centimeter enhancing breast masses on MRI with radiomics and machine learning in BRCA mutation carriers

This retrospective study aimed to investigate whether radiomics features extracted from MRI of BRCA-positive patients with sub-centimeter breast masses can be...

European Radiology

2 years ago

CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma

The authors of this retrospective study aimed to develop and validate a CT-based radiomics model for preoperative prediction of spread through air space...

European Radiology

2 years ago

Machine learning and radiomic phenotyping of lower grade gliomas: improving survival prediction

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...

European Radiology

3 years ago

AI abstracts from ECR 2019: analysis of topics and compliance with the STARD for abstracts checklist

New machine learning techniques, especially deep neural networks, hold the promise of revolutionizing many aspects of radiology and have gained immense public...

Daniel Pinto dos Santos

3 years ago

Diagnostic accuracy and potential covariates for machine learning to identify IDH mutations in glioma patients: evidence from a meta-analysis

The goal of this study was to assess the diagnostic accuracy of machine learning in the prediction of isocitrate dehydrogenase (IDH) mutations, particularly...

European Radiology

3 years ago