A practical guide to the implementation of AI in orthopaedic research—Part 7: Risks, limitations, safety and verification of medical AI systems
Reviewartikel, 2025
Artificial intelligence (AI) has been influencing healthcare and medical research for several years and will likely become indispensable in the near future. AI is intended to support healthcare professionals to make the healthcare system more efficient and ultimately improve patient outcomes. Despite the numerous benefits of AI systems, significant concerns remain. Errors in AI systems can pose serious risks to human health, underscoring the critical need for safety, as well as adherence to ethical and moral standards, before these technologies can be integrated into clinical practice. To address these challenges, the development, certification, and deployment of medical AI systems must adhere to strict and transparent regulations. The European Commission has already established a regulatory framework for AI systems by enacting the European Union Artificial Intelligence Act. This review article, part of an AI learning series, discusses key considerations for medical AI systems such as reliability, accuracy, trustworthiness, lawfulness and legal compliance, ethical and moral alignment, sustainability, and regulatory oversight. Level of Evidence: Level V.
standards
AI
future
risk
healthcare
digitalization
safety
certification
Författare
Philipp W. Winkler
Johannes Kepler Universität Linz (JKU)
Göteborgs universitet
Sahlgrenska universitetssjukhuset
Bálint Zsidai
Göteborgs universitet
Sahlgrenska universitetssjukhuset
Eric Hamrin Senorski
Göteborgs universitet
Sahlgrenska universitetssjukhuset
James Pruneski
Tripler Regional Med Center
Michael T. Hirschmann
Kantonsspital Baselland
Universität Basel
Christophe Ley
Université du Luxembourg
Thomas Tischer
Malteser Waldkrankenhaus Erlangen
Universität Rostock
Elmar Herbst
Universität Münster
Ayoosh Pareek
Hospital for Special Surgery - New York
Volker Musahl
UPMC Sports Medicine
Jacob F. Oeding
Göteborgs universitet
Mayo Clinic Alix School of Medicine
Felix C. Oettl
Universität Zürich
Umile Giuseppe Longo
Università Campus Bio-Medico di Roma
Fondazione Policlinico Universitario Campus Bio-Medico
Kristian Samuelsson
Sahlgrenska universitetssjukhuset
Göteborgs universitet
Robert Feldt
Chalmers, Data- och informationsteknik, Software Engineering
Journal of Experimental Orthopaedics
2197-1153 (eISSN)
Vol. 12 2 e70247Ämneskategorier (SSIF 2025)
Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi
Medicinsk etik
DOI
10.1002/jeo2.70247
PubMed
40276496