{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T18:57:01Z","timestamp":1792090621871,"version":"4.4.0"},"reference-count":26,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T00:00:00Z","timestamp":1781049600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Digit. Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The European Union AI Act [Regulation (EU) 2024\/1689] establishes the first comprehensive legal framework for artificial intelligence. While AI offers transformative potential in healthcare, its deployment introduces risks regarding safety, bias, and accountability. There is currently a lack of practical operational frameworks to help healthcare facilities transition from legal theory to clinical compliance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We performed a qualitative regulatory analysis of the EU AI Act, specifically focusing on the obligations of \u201cdeployers\u201d (Articles 26, 27, and 50) in clinical settings. The Act's requirements were cross-referenced with established clinical governance standards (e.g., MDR 2017\/745 and FUTURE-AI guidelines). A 10-step compliance roadmap was synthesized and exemplified through a hypothetical case study of a high-risk multimodal breast cancer AI system.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The analysis identifies healthcare as a primary focus of the Act, with most clinical AI tools classified as \u201chigh-risk\u201d. We established a four-phase implementation framework: (1) Foundational Strategy and Governance, (2) System Analysis &amp;amp; Risk Assessment, (3) Operational Integration, and (4) Ongoing Compliance. Key results include the definition of mandatory Fundamental Rights Impact Assessments (FRIA), requirements for site-specific technical validation, and the necessity of establishing trust through structured human oversight mechanisms to mitigate automation bias.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The EU AI Act necessitates a shift from transactional procurement to a lifecycle-spanning compliance partnership between vendors and hospitals. While the administrative burden is substantial, the Act provides the essential framework for the safe scaling of medical AI. Proactive alignment with these standards, particularly regarding AI literacy and human oversight, is a strategic necessity for healthcare facilities to ensure patient safety and regulatory readiness by the August 2026 enforcement deadline.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fdgth.2026.1808373","type":"journal-article","created":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T14:02:02Z","timestamp":1781100122000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["The EU AI Act: implications and compliance guidance for healthcare facilities"],"prefix":"10.3389","volume":"8","author":[{"given":"Fabio","family":"Dennst\u00e4dt","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology, Inselspital, Bern University Hospital and University of Bern","place":["Bern, 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