Artificial intelligence in publications: an interview with Professor Yves Menu

Throughout this series, we will get an inside look at the topic of artificial intelligence (AI) in relation to radiological journals over three brief interviews with the Editors-in-Chief of the European Society of Radiology’s three flagship journals: European Radiology (Professor Yves Menu), European Radiology Experimental (Professor Francesco Sardanelli), and Insights into Imaging (Professor Luis Martí-Bonmatí). This week, we begin with Professor Yves Menu, Editor-in-Chief of European Radiology, who has been Editor-in-Chief since 2017 and currently resides in Paris, France.

What Artificial Intelligence-related trends are you seeing in the field of radiology at the moment?

Globally, we see an increasing proportion of submissions dealing with artificial intelligence (AI). Today, they account for 20-30% of all submissions. I expect that we will reach 50% in the near future; however, AI will not necessarily be the main topic of the study, but conversely used as a method of image analysis.

Which topics and (clinical) questions within artificial intelligence are currently the most prominent in your journal (e.g. machine learning, convolutional neural networks, computer-aided diagnosis, etc.)?

Machine learning, convolutional neural networks, etc. are tools, not clinical questions; they are tentative methods to answer these questions. I would say that today, we are half-way between technical considerations, such as “which is the best machine learning algorithm for image analysis”, and clinical questions, such as “how can this method help me predict a tumor grade or lymph node involvement”. Most manuscripts explore the possibility of AI and try to validate specific methods to achieve a clinical task; however, these papers are still very focused. Researchers are working hard to improve their methodology; for example, enlarging samples as much as possible, clarifying algorithms, and producing relevant validation. This rather technical step will remain necessary until our readership becomes familiar with the new vocabulary and learns how to evaluate the robustness of publications by themselves.

By the way, this again stresses the importance of multicentric cooperation for validation, as the machines faithfully reproduce the human work in the sense that each center defines its own “subjective truth”, not necessarily identical to that of another institution.

The vast majority of submissions deal with image analysis using non-visible data embedded within images, and/or comparison with a large database, in order to analyze the image better than a human could. An emerging question is whether or not AI needs images to analyze the signal. Images are reconstructed for the human eye, not for the machine. What if the machine can analyze raw data? However, there are other applications, starting with the improvement of image production, at the reconstruction level, opening a new perspective in further reducing the radiation dose while improving the image quality for the human eye.

Finally, we start seeing some attempts to use AI in order to improve our organization. If it is still at the very beginning in our environment, it is already a prominent issue outside the medical world.

In which area do you think AI is quite advanced, and in which areas will further research be needed?

I don’t know about any field that would not need further research. AI obviously needs further research – and in all directions.

From a methodological point of view, AI methods should be clarified and shared. Regarding statistics, and even if all of us are not, by far, expert statisticians, we have some common basic knowledge, like significance level or intraclass correlation, for example. AI methods still need to be better understood and shared, and probably standardized. We are not yet there.

Clinical applications are promising; however, they are still very focused. AI methods need to widen their scope and probably be integrated with basic tools. Do we need a program that only predicts lymph nodes’ involvement of squamous cell head and neck cancers? Probably not, as we would ask the AI to help us on a more global scale for the diagnosis and the management of these tumors, including detection, characterization, prognosis evaluation, and response to treatment.

In the near future, we can expect the integration of various solutions into a limited number of software programmes. Day after day, we are approaching the conclusion that AI has the potential to become the most efficient assistant we could ever dream of. Conversely, we will have to learn how to remain the ‘Master of Ceremony’.


Latest posts

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.


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.

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.

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.

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



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.

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