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AI competency in European medical physics education and training

Source article: The medical physicist's role in the artificial intelligence era: an updated EFOMP curricular and professional framework

Purpose Five years after the European Federation of Organizations for Medical Physics (EFOMP) published its first curricular framework for artificial intelligence (AI) in medical physics, the updated core curricula for radiology, radiotherapy and nuclear medicine have incorporated AI as a core competency rather than an addendum, a change consistent with the framework's principal recommendation. This paper examines the resulting educational landscape and defines the next stage of AI competency for the profession.…

By the Truvace desk2 min read1 sourcePeer-reviewedTRV-2026-1858· cite & verify
The medical physicist's role in the artificial intelligence era: an updated EFOMP curricular and professional framework
Hospital Universitari Doctor Peset, València 10 by 19Tarrestnom65. CC BY-SA 4.0 · https://creativecommons.org/licenses/by-sa/4.0
Trace impact readingContested
P 66The P score combines the specificity and measured human impact of the grounded problem claim with the strength of this Trace’s cited sources.

Both sides are scored from claims and sources, not community votes.

G 65The G score combines the specificity and measured human impact of the grounded gain claim with the strength of this Trace’s cited sources.

In brief

Five years after the European Federation of Organizations for Medical Physics published its first AI curricular framework, a working group reviewed the 2021 white paper and three updated core curricula. It found that AI is now a core competency in radiology, radiotherapy and nuclear medicine training, though the curricula differ in how much credit and detail they give it.

The work matters because the profession's task has shifted from showing that AI is important to integrating it safely and in line with regulation in clinical practice. What is still open is how far the proposed advanced framework will be adopted by national organizations, training centers and practitioners, since the paper presents recommendations rather than measured patient outcomes.

Main points

  1. The curricula share a methodological foundation but differ in ECTS allocation, coverage of recent AI architectures and treatment of the EU AI Act.
  2. A proposed advanced framework covers four domains: validation and quality assurance, AI lifecycle management, generative AI and foundation models, and governance.
  3. A professional lifecycle model sets out how competencies are acquired in specialist training, maintained through accredited continuing development and formally recognized.
  4. The medical physicist's responsibilities under the EU AI Act are defined and turned into recommendations for EFOMP, national organizations, training centers and individuals.

The gain

The updated EFOMP radiology, radiotherapy and nuclear medicine curricula now treat AI as a core competency, which supports safer clinical integration of AI.

The problem

Six competency gaps common to all three medical physics subspecialties remain beyond the entry-level curricula, and the curricula diverge in ECTS allocation, coverage of recent AI architectures and treatment of the EU AI Act.

The rundown

The analysis used comparative curriculum analysis, competency mapping, regulatory analysis and iterative expert deliberation within Focus Group 3 of the EFOMP AI Special Interest Group. Its scope was predefined and covered depth of treatment, terminology, regulatory references and recent AI developments.

Competency gaps beyond entry level were written in the knowledge-skills-competence format used in EFOMP curricula. The framework drew on three large surveys of medical physicists from 2020, 2024 and 2025 and was reviewed within the working group before consultation with the EFOMP community.

What this doesn’t fix

The study is a expert-deliberation and curriculum-comparison exercise, so it offers a proposed framework and recommendations rather than evidence of outcomes for patients or practice.

Sources

  1. Peer-reviewedPhysica Medica2026-10-05

The debate