ArticleAbdominal radiology (New York)2026
The AI Act and the MDR post-market requirements for semiautonomous AI SaMD: a radiology case study in prostate cancer.
Article in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed.
- Large language models and prostate MRI reporting: a stringent testbed for safe deployment under evolving AI, health-data, and cybersecurity regulation.Abdominal radiology (New York) · 2026Review
- Autonomous AI in prostate cancer: the road ahead towards clinical implementation.Abdominal radiology (New York) · 2026Review
- Uncertainty quantification for artificial intelligence in medical imaging: what every radiologist needs to know.Abdominal radiology (New York) · 2026Review
- Standardizing PSMA PET/CT reporting in prostate cancer: from structured frameworks to AI-assisted interpretation.Abdominal radiology (New York) · 2026Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo clarify overlapping post-market obligations under the EU Artificial Intelligence Act (AIA) and EU Medical Device Regulation (MDR) for high-risk artificial intelligence (AI) Software as a Medical Device (SaMD), and to map the regulatory landscape for manufacturers, healthcare providers, AI providers, and AI deployers.
methodsWe conducted a qualitative doctrinal legal analysis of post-market provisions in the AIA and MDR, using a case study of a high-risk Class III AI SaMD for prostate cancer radiology. No empirical clinical or performance data were collected. The analysis focused on key stakeholders, including device manufacturers and deployers (e.g., healthcare providers). We sought to identify (1) convergence, where both regulations impose overlapping or complementary requirements, and (2) divergence, where obligations are addressed by only one regulation, revealing potential regulatory gaps.
resultsWe organized the extracted post-market obligations into ten categories. Overall, both regulations place increasing emphasis on lifecycle traceability and continuous monitoring. We identified convergence in areas such as documentation and performance monitoring, while divergences emerged in domains like human oversight (in the AIA) and reporting non-serious patterns (in the MDR). We also identified gaps in regulatory guidance, particularly regarding system updates, human oversight, and the evolving responsibilities of healthcare providers.
conclusionThe AIA and MDR share common ground in some post-market areas but also diverge in key responsibilities. To ensure safe and effective use of high-risk AI in healthcare, clearer coordination between the two frameworks is needed, especially in areas such as human oversight and system modification, where current guidance remains limited.
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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.