A practical guide to the implementation of AI in orthopaedic research—Part 7: Risks, limitations, safety and verification of medical AI systems
Abstract 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 outcome...
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| Format: | Article |
| Language: | English |
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Wiley
2025-04-01
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| Series: | Journal of Experimental Orthopaedics |
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| Online Access: | https://doi.org/10.1002/jeo2.70247 |
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| author | Philipp W. Winkler Bálint Zsidai Eric Hamrin Senorski James A. Pruneski Michael T. Hirschmann Christophe Ley Thomas Tischer Elmar Herbst Ayoosh Pareek Volker Musahl Jacob F. Oeding Felix C. Oettl Umile Giuseppe Longo Kristian Samuelsson Robert Feldt ESSKA Artificial Intelligence Working Group |
| author_facet | Philipp W. Winkler Bálint Zsidai Eric Hamrin Senorski James A. Pruneski Michael T. Hirschmann Christophe Ley Thomas Tischer Elmar Herbst Ayoosh Pareek Volker Musahl Jacob F. Oeding Felix C. Oettl Umile Giuseppe Longo Kristian Samuelsson Robert Feldt ESSKA Artificial Intelligence Working Group |
| author_sort | Philipp W. Winkler |
| collection | DOAJ |
| description | Abstract 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. |
| format | Article |
| id | doaj-art-3da85b22ed64476a9dd732c6c28c7137 |
| institution | Kabale University |
| issn | 2197-1153 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Experimental Orthopaedics |
| spelling | doaj-art-3da85b22ed64476a9dd732c6c28c71372025-08-20T04:03:13ZengWileyJournal of Experimental Orthopaedics2197-11532025-04-01122n/an/a10.1002/jeo2.70247A practical guide to the implementation of AI in orthopaedic research—Part 7: Risks, limitations, safety and verification of medical AI systemsPhilipp W. Winkler0Bálint Zsidai1Eric Hamrin Senorski2James A. Pruneski3Michael T. Hirschmann4Christophe Ley5Thomas Tischer6Elmar Herbst7Ayoosh Pareek8Volker Musahl9Jacob F. Oeding10Felix C. Oettl11Umile Giuseppe Longo12Kristian Samuelsson13Robert Feldt14ESSKA Artificial Intelligence Working GroupDepartment for Orthopaedics and Traumatology Kepler University Hospital GmbH, Johannes Kepler University Linz Linz AustriaDepartment of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy University of Gothenburg Gothenburg SwedenSahlgrenska Sports Medicine Center Göteborg SwedenDepartment of Orthopaedic Surgery Tripler Army Medical Center Honolulu Hawaii USADepartment of Orthopaedic Surgery and Traumatology Kantonsspital Baselland Bruderholz SwitzerlandDepartment of Mathematics University of Luxembourg Esch‐sur‐Alzette LuxembourgDepartment of Orthopaedic Surgery University Medicine Rostock Rostock GermanyDepartment of Trauma Hand and Reconstructive Surgery, University Hosptial Muenster Münster GermanySports Medicine and Shoulder Institute Hospital for Special Surgery New York New York USADepartment of Orthopaedic Surgery, UPMC Freddie Fu Sports Medicine Center University of Pittsburgh Pittsburgh Pennsylvania USADepartment of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy University of Gothenburg Gothenburg SwedenDepartment of Orthopedic Surgery Balgrist University Hospital, University of Zürich Zurich SwitzerlandFondazione Policlinico Universitario Campus Bio‐Medico Roma ItalyDepartment of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy University of Gothenburg Gothenburg SwedenDepartment of Computer Science and Engineering Chalmers University of Technology Gothenburg SwedenAbstract 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.https://doi.org/10.1002/jeo2.70247AIcertificationdigitalizationfuturehealthcarerisk |
| spellingShingle | Philipp W. Winkler Bálint Zsidai Eric Hamrin Senorski James A. Pruneski Michael T. Hirschmann Christophe Ley Thomas Tischer Elmar Herbst Ayoosh Pareek Volker Musahl Jacob F. Oeding Felix C. Oettl Umile Giuseppe Longo Kristian Samuelsson Robert Feldt ESSKA Artificial Intelligence Working Group A practical guide to the implementation of AI in orthopaedic research—Part 7: Risks, limitations, safety and verification of medical AI systems Journal of Experimental Orthopaedics AI certification digitalization future healthcare risk |
| title | A practical guide to the implementation of AI in orthopaedic research—Part 7: Risks, limitations, safety and verification of medical AI systems |
| title_full | A practical guide to the implementation of AI in orthopaedic research—Part 7: Risks, limitations, safety and verification of medical AI systems |
| title_fullStr | A practical guide to the implementation of AI in orthopaedic research—Part 7: Risks, limitations, safety and verification of medical AI systems |
| title_full_unstemmed | A practical guide to the implementation of AI in orthopaedic research—Part 7: Risks, limitations, safety and verification of medical AI systems |
| title_short | A practical guide to the implementation of AI in orthopaedic research—Part 7: Risks, limitations, safety and verification of medical AI systems |
| title_sort | practical guide to the implementation of ai in orthopaedic research part 7 risks limitations safety and verification of medical ai systems |
| topic | AI certification digitalization future healthcare risk |
| url | https://doi.org/10.1002/jeo2.70247 |
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