disease progression

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

Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data

Although challenging to predict, early recognition of COVID-19 severity can help guide patient management. The authors of this study aimed to develop an artificial intelligence system that was capable of predicting future deterioration to critical illness in COVID-19 patients. The AI system was developed to integrate chest CT and clinical data for risk prediction of said future deterioration to critical

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From community-acquired pneumonia to COVID-19: a deep learning–based method for quantitative analysis of COVID-19 on thick-section CT scans

In this retrospective study, the authors aimed to develop a fully automated artificial intelligence (AI) system to quantitatively assess the severity and progression of COVID-19 using thick-section chest CT images. Through their research and work, they were able to determine that a deep learning-based AI system built on thick-section CT imaging can accurately quantify COVID-19-associated abnormalities in the lung and

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Noncontrast computer tomography–based radiomics model for predicting intracerebral hemorrhage expansion: preliminary findings and comparison with conventional radiological model

The authors developed a radiomics model for predicting hematoma expansion in patients with intracerebral haemorrhage (ICH) and compared its predictive performance with a conventional radiological feature-based model. Through retrospective analysis and noncontrast computed tomography (NCCT) assessment, it was found that an NCCT-based radiomics model showed better performance in the prediction of early hematoma expansion in ICH patients. Key points Radiomics

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Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data

Although challenging to predict, early recognition of COVID-19 severity can help guide patient management. The authors of this study aimed to develop an artificial intelligence system that was capable of predicting future deterioration to critical illness in COVID-19 patients. The AI system was developed to integrate chest CT and clinical data for risk prediction of said future deterioration to critical

Read More →

From community-acquired pneumonia to COVID-19: a deep learning–based method for quantitative analysis of COVID-19 on thick-section CT scans

In this retrospective study, the authors aimed to develop a fully automated artificial intelligence (AI) system to quantitatively assess the severity and progression of COVID-19 using thick-section chest CT images. Through their research and work, they were able to determine that a deep learning-based AI system built on thick-section CT imaging can accurately quantify COVID-19-associated abnormalities in the lung and

Read More →

Noncontrast computer tomography–based radiomics model for predicting intracerebral hemorrhage expansion: preliminary findings and comparison with conventional radiological model

The authors developed a radiomics model for predicting hematoma expansion in patients with intracerebral haemorrhage (ICH) and compared its predictive performance with a conventional radiological feature-based model. Through retrospective analysis and noncontrast computed tomography (NCCT) assessment, it was found that an NCCT-based radiomics model showed better performance in the prediction of early hematoma expansion in ICH patients. Key points Radiomics

Read More →

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  • Reduced registration fees for ECR 1
  • Option to participate in the European Diploma. 3
  • Free electronic access to the journal European Radiology
  • Content e-mails for all ESR journals 4
  • Updates on offers & events through our newsletters
  • Exclusive access to the ESR feed in Juisci

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Footnotes:

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

02
Not all activities included
03
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04
European Radiology, Insights into Imaging, European Radiology Experimental.