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Back to main AI Blog

prognosis

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:

machine learningdeep learningradiomicsmrix-ray computed tomographyai newsCOVID-19interviewmammographybreast cancerdiagnostic imagingneural networkstomographyradiographyMDCTworkflow

Latest posts

New radiomics model to predict the Leibovich risk groups for ccRCC patients

Insights into Imaging March 2024

This study developed and validated a triphasic CT-based radiomics model, which incorporated radiomics features and significant clinical factors, for preoperative risk stratification of patients with localized clear cell renal cell carcinoma (ccRCC). The model showed a favorable performance in preoperatively predicting the Leibovich low-risk and intermediate-high-risk groups in localized ccRCC patients. The authors determined that this model can be used

Read More →

Radiomics in the evaluation of ovarian masses

Insights into Imaging February 2024

This systematic review looked at the literature reporting the application of radiomics to imaging techniques in ovarian lesion patients. The authors found that radiomics showed promising results and great potential as a clinical diagnostic tool in patients with ovarian masses when it comes to improving lesion stratification, treatment selection, and outcome prediction. However, much larger and more diverse patient cohorts

Read More →

Radiomic assessment of oesophageal adenocarcinoma

Insights into Imaging August 2022

The use of radiomic models offers a possible way to improve oesophageal adenocarcinoma assessment through quantitative image analysis, but model selection becomes complicated due to the myriad available predictors as well as the uncertainty of their relevance and reproducibility. Therefore, the aim of this study was to review recent research in order to facilitate precedent-based model selection for prospective validation

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 →

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

European Radiology September 2020

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 →

Can radiomics improve the prediction of metastatic relapse of myxoid/round cell liposarcomas?

European Radiology March 2020

In this study, the authors aimed to improve the prediction of patients’ prognosis of myxoid/round cell liposarcomas (MRC-LPS) using a radiomics approach. 35 patients with MRC-LPS were included in this retrospective study. They found that the best prediction of metastatic relapse-free survival for MRC-LPS was achieved by combining the radiomics score to relevant radiological features. Key points Fourteen radiomics features

Read More →

New radiomics model to predict the Leibovich risk groups for ccRCC patients

Insights into Imaging March 2024

This study developed and validated a triphasic CT-based radiomics model, which incorporated radiomics features and significant clinical factors, for preoperative risk stratification of patients with localized clear cell renal cell carcinoma (ccRCC). The model showed a favorable performance in preoperatively predicting the Leibovich low-risk and intermediate-high-risk groups in localized ccRCC patients. The authors determined that this model can be used

Read More →

Radiomics in the evaluation of ovarian masses

Insights into Imaging February 2024

This systematic review looked at the literature reporting the application of radiomics to imaging techniques in ovarian lesion patients. The authors found that radiomics showed promising results and great potential as a clinical diagnostic tool in patients with ovarian masses when it comes to improving lesion stratification, treatment selection, and outcome prediction. However, much larger and more diverse patient cohorts

Read More →

Radiomic assessment of oesophageal adenocarcinoma

Insights into Imaging August 2022

The use of radiomic models offers a possible way to improve oesophageal adenocarcinoma assessment through quantitative image analysis, but model selection becomes complicated due to the myriad available predictors as well as the uncertainty of their relevance and reproducibility. Therefore, the aim of this study was to review recent research in order to facilitate precedent-based model selection for prospective validation

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 →

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

European Radiology September 2020

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 →

Can radiomics improve the prediction of metastatic relapse of myxoid/round cell liposarcomas?

European Radiology March 2020

In this study, the authors aimed to improve the prediction of patients’ prognosis of myxoid/round cell liposarcomas (MRC-LPS) using a radiomics approach. 35 patients with MRC-LPS were included in this retrospective study. They found that the best prediction of metastatic relapse-free survival for MRC-LPS was achieved by combining the radiomics score to relevant radiological features. Key points Fourteen radiomics features

Read More →

Become A Member Today!

You will have access to a wide range of benefits that can help you advance your career and stay up-to-date with the latest developments in the field of radiology. These benefits include access to educational resources, networking opportunities with other professionals in the field, opportunities to participate in research projects and clinical trials, and access to the latest technologies and techniques. 

Check out our different membership options.

If you don’t find a fitting membership send us an email here.

①

Membership

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

  • Reduced registration fees for ECR 1
  • Reduced fees for the European School of Radiology (ESOR) 2
  • Exclusive option to participate in the European Diploma. 3
  • Free electronic access to the journal European Radiology 4
  • Content e-mails for all ESR journals
  • Updates on offers & events through our newsletters
  • Exclusive access to the ESR feed in Juisci

€ 11 /year

Yes! That is less than €1 per month.
②

Free membership

for radiologists, radiology residents or professionals of allied sciences engaged in practice, teaching or research residing outside Europe as well as individual qualified professionals with an interest in radiology and medical imaging who do not fulfil individual or all requirements for any other ESR membership category & former full members who have retired from all clinical practice
  • Reduced registration fees for ECR 1
  • Free electronic access to the journal European Radiology
  • Content e-mails for all 3 ESR journals 4
  • Updates on offers & events through our newsletters
  • Exclusive access to the ESR feed in Juisci

€ 0

The best things in life are free.
③

ESR Friends

For students, company representatives or hospital managers etc.

  • Content e-mails for all 3 ESR journals 4
  • Updates on offers & events through our newsletters

€ 0

Friendship doesn’t cost a thing.
Apply now

The membership type best fitting for you will be selected automatically during the application process.

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
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.