Artificial intelligence in radiology workflow: from concept to experience

15 - 17 Nov 2023

100% Online

Level II - General radiologist

10.5 EACCME CME Credits

In this 3-day hands-on radiology course with two AI experts, Prof. Erik Ranschaert and Dr. Mohammad H. Rezazade Mehrizi, participants will experience working with various forms of AI, reflect on their own experience, and gain practical experience from it. Radiologists will learn how to adapt to using such tools, how to re-organise their workflow when using one or more an AI-applications, and how they can actively engage in making such implementation a success.

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Much has been said about the potential of artificial intelligence in the medical imaging domain and in radiology work in particular. It is time to move from just talking about it and “experience” how it may appear in our work, and how we can bring it effectively to our work. This is the focus of this training program: together we experience working with various forms of AI, reflect on our experience, and gain practical experience from it.

This Artificial Intelligence radiology fellowship operates on the principles of “reflective” and “experiential” learning and offers you the chance to come on the stage and experience what you may have heard about it. It does NOT require any technical knowledge, nor does it demand you to do much preparation before the training. However, it does require your mindful presence and active engagement during the sessions.

Day 1: Fundamental module: How to get started and engage with AI
Day 2: Operating module: How to mindfully work with AI
Day 3: Mastery module: How to critically operate and supervise AI

TMC Academy fellowships are held in a virtual classroom environment on Zoom. Participants are encouraged to engage in discussions making use of their camera and microphone in order to recreate the face-to-face experience.

In this small group environment among your peers, you are free to ask questions, engage in discussions, and learn together with the support of the mentors.

Participants will be asked to fill in a pre-course survey to help the speakers evaluate the knowledge and experience of the participants, thus creating a more personalized and relevant programme.


"A very well thought of, designed, and carried out course showing many aspects about the use of AI in the current radiological work-up of patients.”
Dr. B Gomez-Anson, TMC Neuroradiologist. Clinical Head of Neuroradiology, Hospital Sant Pau, Barcelona. (Fellow, Nov 2022)

"This fellowship gives a good basic insight in what AIs are available of today and a general understanding of the uses and limitations in the field at the moment, but most importantly a guided approach to careful and proper use of the tools in regard of pitfalls both in the tools and the users. It's relevant to any radiologist who works or want to work with AI in their daily practice and need a basic introduction - excellent speakers and excellent and entertaining execution.”
Dr. Katherine Ann McLean, TMC Radiologist at Body and Emergency Sections, Denmark (Fellow, Nov 2022)

"This fellowship provided a good introduction to the basic concepts of AI and also showcased how to evaluate, implement, and assess the performance of AI solutions for radiology with an emphasis on workflow impacts. Very interactive and hands-on.”
Dr. Olusola Patrick Bello, Consultant Radiologist, Telemedicine Clinic (Fellow, Nov 2022)

Learning objectives

  • Learn how various AI applications can support radiological workflow
  • Learn how to initiate working with an AI tool and configure it appropriately
  • Experience working with of AI tools for conducting various forms of medical tasks
  • Gain the capability to critically reflect on the results of working with AI tools at work
  • Learn how to supervise working with AI and properly integrate it to the workflow

Programme will include

  • Hands-on experience with various AI tools
  • Extensive practical exercises related to different medical tasks and clinical conditions
  • Receiving direct and reflective feedback combined with first-hand experience
  • Learning from peers and sharing expertise with other peers
  • Certificate of attendance - An application has been made to the UEMS/EBR for CME accreditation of this event


Level II - General radiologist
This fellowship is suitable for all radiologists including all sub-specialties and residents, especially radiologists with interest in Imaging Informatics and AI, or radiologists and medical managers willing to embrace innovations into the work and career of their teams

Group Discounts
TMC Academy is happy to offer group discounts to support radiology education within hospitals or practices. Please email us at for details.

Technical requirements

The training platform runs entirely in the browser but the online PACS places a considerable load on the hardware and internet connection when viewing and loading cases.

Hardware Tablets * Minimum Recommended
Memory (RAM): 2 Gigabyte 8 Gigabyte 16 Gigabyte
Processor (CPU): Dual core 1.85 Ghz Dual core 2 Ghz Quad core 2.5 Ghz
Internet connection Minimum Recommended
Speed: 10 Mbps 25 Mbps
Software Tablets Desktop
Browser: Safari * Chrome **
  • * Tested with Safari on iPad 9.7 (2017), should also work on Android with Chrome. User interface not optimized for smaller screens. Large cases (more than 600 images) are not able to be opened on tablet or mobile devices due to memory constraints.
  • ** Firefox, Edge and Safari also work but might not provide an equally smooth experience. Internet Explorer is not supported.


  • Mohammad H. Rezazade Mehrizi Ph.D.
    Amsterdam, Netherlands

    Associate Professor, School of Business and Economics, Knowledge, Information and Innovation, KIN Center for Digital Innovation, Vrije Universiteit Amsterdam

  • Prof. Erik Ranschaert M.D. Ph.D.
    Ghent, Belgium

    Visiting Professor at Ghent University, Belgium Radiologist at St. Nikolaus Hospital in Eupen, Belgium Member of AI Centre of Excellence, Unilabs Past-president of EuSoMII, advisor for several companies in the domain of AI


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Wednesday - November 15th 2023
13:30 - 13:45 (GMT +0100) Introduction Introduction
13:45 - 14:00 (GMT +0100) Lecture + Hands-on session: Refreshing on the basics of AI: basic concepts such as accuracy, stability, AUC, False-positive, false-negative … Mohammad H. Rezazade Mehrizi
14:00 - 14:30 (GMT +0100) Lecture + Hands-on session: Introducing the range and diversity of the AI applications (Technography study) Prof. Erik Ranschaert
14:45 - 15:00 (GMT +0100) Break Break
15:00 - 16:00 (GMT +0100) Lecture + Hands-on session: Showcasing some ways of implementing and working with AI Mohammad H. Rezazade Mehrizi
16:00 - 17:30 (GMT +0100) Lecture + Hands-on session: How to initiate working with AI: from the first day that it is coming to our desk, what do we need to do and how to work with it and what decisions are involved? Prof. Erik Ranschaert
Thursday - November 16th 2023
13:30 - 14:15 (GMT +0100) Lecture + Hands-on session: Experiencing how to work with different AI applications, on various clinical use-cases and under different working scenarios Mohammad H. Rezazade Mehrizi
14:15 - 15:00 (GMT +0100) Lecture + Hands-on session: AI tools related to different subspecialties (e.g., general radiology, skeletal, and prostate, …) Prof. Erik Ranschaert
15:00 - 15:15 (GMT +0100) Break Break
15:15 - 16:00 (GMT +0100) Lecture + Hands-on session: AI tools with different functionalities and features (e.g., diagnosing, screening, segmenting, measurement) Prof. Erik Ranschaert
16:00 - 16:45 (GMT +0100) Lecture + Hands-on session: Different types of medical use cases (e.g., simple/complex) Mohammad H. Rezazade Mehrizi
16:45 - 17:30 (GMT +0100) Lecture + Hands-on session: Under different working conditions (e.g., time-pressure, 1st vs. 2nd reader, individual vs. collective) Prof. Erik Ranschaert
Friday - November 17th 2023
13:30 - 15:00 (GMT +0100) Lecture + Hands-on session: Critical assessment of AI outcomes: issues, failures, suspicious cases - Critical assessment of AI features/parameters/settings/configurations - How to select your partner and shape it - How to monitor your partner in the long-run (data shift …) Mohammad H. Rezazade Mehrizi
15:00 - 15:15 (GMT +0100) Break Break
15:15 - 16:15 (GMT +0100) Lecture + Hands-on session: How to report and communicate the results of AI? - Using AI in interactions with other medical colleagues and interdisciplinary discussions - Interpretation and explanations to the patients Prof. Erik Ranschaert
16:15 - 17:15 (GMT +0100) Lecture + Hands-on session: Organizational and workflow impacts and how to prepare them - What infrastructure do you need? - Whom do you need to involve? - How to bring people on board? - Ethical and Legal considerations (data sharing , …)? - What training do you need to have? Mohammad H. Rezazade Mehrizi
Prof. Erik Ranschaert
17:15 - 17:30 (GMT +0100) Q&A and closing

Cancellation Policy

What is the cancellation/refund policy?

TMC Academy offers a 7-day money back guarantee from the moment of the online fellowship purchase. 

How do I request a refund?

Send us an email at and we will process your refund.