survival

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.

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Latest posts

Radiomics risk score may be a potential imaging biomarker for predicting survival in isocitrate dehydrogenase wild-type lower-grade gliomas

This study aimed to evaluate whether radiomics from magnetic resonance imaging (MRI) would allow for the prediction of the overall survival in patients with isocitrate dehydrogenase wild-type (IDHwt) lower-grade gliomas. The authors of this study also investigated the added prognostic value of radiomics over clinical features. The authors found that radiomics has the potential for noninvasive risk stratification and can

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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 gliomas over clinical isocitrate dehydrogenase (IDH) status. The authors extracted radiomic features from the preoperative MRI data of 296 lower grade glioma patients from their institution as well as The Cancer Genome Atlas (TCGA) and The

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Radiomics risk score may be a potential imaging biomarker for predicting survival in isocitrate dehydrogenase wild-type lower-grade gliomas

This study aimed to evaluate whether radiomics from magnetic resonance imaging (MRI) would allow for the prediction of the overall survival in patients with isocitrate dehydrogenase wild-type (IDHwt) lower-grade gliomas. The authors of this study also investigated the added prognostic value of radiomics over clinical features. The authors found that radiomics has the potential for noninvasive risk stratification and can

Read More →

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 gliomas over clinical isocitrate dehydrogenase (IDH) status. The authors extracted radiomic features from the preoperative MRI data of 296 lower grade glioma patients from their institution as well as The Cancer Genome Atlas (TCGA) and The

Read More →

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Footnotes:

01

Reduced registration fees for ECR 2024:
Provided that ESR 2023 membership is activated and approved by August 31, 2023.

Reduced registration fees for ECR 2025:
Provided that ESR 2024 membership is activated and approved by August 31, 2024.

02
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03
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04
European Radiology, Insights into Imaging, European Radiology Experimental.