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COVID-19

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.

Most used hashtags:

deep learningmachine learningmriradiomicsx-ray computed tomographyinterviewai newsmammographyCOVID-19neural networksdiagnostic imagingbreast cancerworkflowtomographybreast neoplasmsradiography

Latest posts

Evaluating a deep learning software for lung parenchyma characterization in COVID-19 pneumonia

European Radiology Experimental August 2023

The aim of this study was to evaluate the performance of the LungQuant system, which is a deep learning-based software for quantitative analysis of chest CT. LungQuant was evaluated by comparing its results with independent visual evaluations by a group of clinical experts. The results indicated that an automatic quantification tool may be beneficial and contribute to an improved clinical

Read More →

Covid-19 early detection: Neural Networks vs. Radiologists

Insights into Imaging May 2023

The COVID-19 pandemic not only made an impact on the discipline of radiology as a whole but also on how we use specific tools in its detection. This was especially seen in the role of chest radiography when it was utilized as a diagnostic tool at the beginning of the pandemic “when microbiological resources were scarce,” evolving into its use

Read More →

AI system for detecting COVID-19 on chest radiographs in symptomatic patients

European Radiology October 2022

Due to the challenges associated with differentiating COVID-19 from the number of respiratory infections that can appear on chest radiographs (CXR), the authors of this study developed and validated an AI system for COVID-19 detection on presenting CXR. This was achieved by training a deep learning model on nearly 170,000 CXRs, and was subsequently validated on a large international test

Read More →

Commercial AI solutions in detecting COVID‐19 pneumonia in chest CT: not yet ready for clinical implementation?

Daniel Pinto dos Santos January 2022

Thinking back on the last two years, what were the dominant topics of discussion in radiology? Certainly, artificial intelligence (AI) in radiology has sparked a lot of interest and enthusiasm in radiology, and COVID-19, which was a topic nobody could avoid. So, it comes as no surprise that the combination of both topics – i.e. using AI to detect COVID

Read More →

Machine learning automatically detects COVID-19 using chest CTs in a large multicenter cohort

European Radiology December 2021

This retrospective, multi-institutional study investigated machine learning classifiers and interpretable models using chest CT for the detection of COVID-19 and to differentiate this from types of pneumonia, interstitial lung disease (ILD), and normal CTs. The study included 2,446 chest CTs from across 16 different institutions and the authors’ method was found to accurately differentiate COVID-19 from other types of pneumonia,

Read More →

COVID-19 classification of X-ray images using deep neural networks

European Radiology September 2021

The authors of this retrospective study propose a deep learning model for the detection of COVID-19 from chest x-rays (CXRs), as well as a tool for retrieving similar patients according to the model’s results on their CXRs. The data used for training and evaluating this model was collected from inpatients across four different hospitals. The proposed model achieved accuracy of

Read More →

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

European Radiology August 2021

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 →

Development and multicenter validation of a CT-based radiomics signature for predicting severe COVID-19 pneumonia

European Radiology June 2021

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 retrospective collection of 316 COVID-19 patients (246 non-severe and 70 severe cases), which were allocated to training, validation, and testing cohorts. The authors found that the CT-based radiomics signature showed favourable predictive efficacy for

Read More →

Machine learning based on clinical characteristics and chest CT quantitative measurements for prediction of adverse clinical outcomes in hospitalized patients with COVID-19

European Radiology June 2021

In this study, the authors aimed to develop and validate a machine learning model for the prediction of adverse outcomes in hospitalized patients with COVID-19. They discovered that their findings could be used to facilitate the prediction of adverse outcomes in patients with COVID-19, as well as may allow efficient utilization of medical resources and individualized treatment plans for COVID-19

Read More →

Initial chest radiographs and artificial intelligence (AI) predict clinical outcomes in COVID-19 patients: analysis of 697 Italian patients

European Radiology April 2021

The purpose of this retrospective study was to evaluate whether initial chest X-ray (CXR) severity assessed by an AI system may have prognostic utility in patients with COVID-19. The authors determined, through AI- and radiologist-assessed disease severity scores on CXRs obtained on emergency department (ED) presentation, that they were independent and comparable predictors of adverse outcomes in patients with COVID-19.

Read More →

Evaluating a deep learning software for lung parenchyma characterization in COVID-19 pneumonia

European Radiology Experimental August 2023

The aim of this study was to evaluate the performance of the LungQuant system, which is a deep learning-based software for quantitative analysis of chest CT. LungQuant was evaluated by comparing its results with independent visual evaluations by a group of clinical experts. The results indicated that an automatic quantification tool may be beneficial and contribute to an improved clinical

Read More →

Covid-19 early detection: Neural Networks vs. Radiologists

Insights into Imaging May 2023

The COVID-19 pandemic not only made an impact on the discipline of radiology as a whole but also on how we use specific tools in its detection. This was especially seen in the role of chest radiography when it was utilized as a diagnostic tool at the beginning of the pandemic “when microbiological resources were scarce,” evolving into its use

Read More →

AI system for detecting COVID-19 on chest radiographs in symptomatic patients

European Radiology October 2022

Due to the challenges associated with differentiating COVID-19 from the number of respiratory infections that can appear on chest radiographs (CXR), the authors of this study developed and validated an AI system for COVID-19 detection on presenting CXR. This was achieved by training a deep learning model on nearly 170,000 CXRs, and was subsequently validated on a large international test

Read More →

Commercial AI solutions in detecting COVID‐19 pneumonia in chest CT: not yet ready for clinical implementation?

Daniel Pinto dos Santos January 2022

Thinking back on the last two years, what were the dominant topics of discussion in radiology? Certainly, artificial intelligence (AI) in radiology has sparked a lot of interest and enthusiasm in radiology, and COVID-19, which was a topic nobody could avoid. So, it comes as no surprise that the combination of both topics – i.e. using AI to detect COVID

Read More →

Machine learning automatically detects COVID-19 using chest CTs in a large multicenter cohort

European Radiology December 2021

This retrospective, multi-institutional study investigated machine learning classifiers and interpretable models using chest CT for the detection of COVID-19 and to differentiate this from types of pneumonia, interstitial lung disease (ILD), and normal CTs. The study included 2,446 chest CTs from across 16 different institutions and the authors’ method was found to accurately differentiate COVID-19 from other types of pneumonia,

Read More →

COVID-19 classification of X-ray images using deep neural networks

European Radiology September 2021

The authors of this retrospective study propose a deep learning model for the detection of COVID-19 from chest x-rays (CXRs), as well as a tool for retrieving similar patients according to the model’s results on their CXRs. The data used for training and evaluating this model was collected from inpatients across four different hospitals. The proposed model achieved accuracy of

Read More →

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

European Radiology August 2021

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 →

Development and multicenter validation of a CT-based radiomics signature for predicting severe COVID-19 pneumonia

European Radiology June 2021

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 retrospective collection of 316 COVID-19 patients (246 non-severe and 70 severe cases), which were allocated to training, validation, and testing cohorts. The authors found that the CT-based radiomics signature showed favourable predictive efficacy for

Read More →

Machine learning based on clinical characteristics and chest CT quantitative measurements for prediction of adverse clinical outcomes in hospitalized patients with COVID-19

European Radiology June 2021

In this study, the authors aimed to develop and validate a machine learning model for the prediction of adverse outcomes in hospitalized patients with COVID-19. They discovered that their findings could be used to facilitate the prediction of adverse outcomes in patients with COVID-19, as well as may allow efficient utilization of medical resources and individualized treatment plans for COVID-19

Read More →

Initial chest radiographs and artificial intelligence (AI) predict clinical outcomes in COVID-19 patients: analysis of 697 Italian patients

European Radiology April 2021

The purpose of this retrospective study was to evaluate whether initial chest X-ray (CXR) severity assessed by an AI system may have prognostic utility in patients with COVID-19. The authors determined, through AI- and radiologist-assessed disease severity scores on CXRs obtained on emergency department (ED) presentation, that they were independent and comparable predictors of adverse outcomes in patients with COVID-19.

Read More →

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①

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for radiologists, radiology residents, professionals of allied sciences (including radiographers/radiological technologists, nuclear medicine physicians, medical physicists, and data scientists) & professionals of allied sciences in training residing within the boundaries of Europe

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  • Option to participate in the European Diploma. 3
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  • Content e-mails for all ESR journals4
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  • Exclusive access to the ESR feed in Juisci

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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:

01

Reduced registration fees for ECR 2026:
Provided that ESR 2025 membership is activated and approved by August 31, 2025.

02
Not all activities included
03
Examination based on the ESR European Training Curriculum (radiologists or radiology residents).
04
European Radiology, Insights into Imaging, European Radiology Experimental.