Evidence map›Paper›PMID 42825232›Full record

ReviewBMJ digital health & AI2026

High-risk without safeguards? The EU AI Act and the push for deregulation of medical AI.

Hannah Van Kolfschooten, Barry Solaiman, Daria Onitiu

Abstract readReview
In one paragraph

Review in BMJ digital health & AI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hannah Van KolfschootenCenter for Life Sciences Law, University of Basel, Basel, Switzerland.ORCID https://orcid.org/0000-0002-3342-0285
Barry SolaimanHarvard Medical School Center for Bioethics, Boston, Massachusetts, USA.
Daria OnitiuHasso-Plattner-Institut fur Digital Engineering gGmbH, Potsdam, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is increasingly embedded in clinical decision-making, yet recent proposals to simplify the European Union (EU) Artificial Intelligence Act (AI Act) have reopened the question of whether AI-enabled medical devices should remain subject to the AI Act's full high-risk regime. Under the current framework, AI-enabled medical devices are regulated through a combination of sectoral medical device legislation (the Medical Devices Regulation (MDR) and In Vitro Diagnostic Medical Devices Regulation (IVDR)) and additional AI-specific safeguards contained in the AI Act. This narrative review analyses the Health Innovation Package and related legislative developments under the EU simplification agenda and examines their impact on the relationship between the AI Act and medical device law. It shows that the proposed reform would retain the high-risk classification of AI-enabled medical devices while removing most associated AI Act obligations. In effect, this decouples risk classification from the safeguards that give it regulatory meaning, including requirements on data governance, risk management, human oversight and postmarket monitoring. Rather than resolving regulatory overlap, the amendments shift the centre of gravity back to product-focused medical device law without ensuring equivalent AI-specific safeguards. These changes may narrow attention to fundamental rights, weaken oversight in clinical use and increase legal uncertainty regarding accountability and responsibility. In a domain where AI systems directly shape clinical decisions and patient outcomes, these changes risk undermining the conditions for safe, equitable and accountable deployment of medical AI.

Indexed as

Artificial intelligenceClinical GovernanceHealth EquityPatient CareStandard of Care

Identifiers

PMID42825232
PMCPMC13629938

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.