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      Orthopaedic surgeons display a positive outlook towards artificial intelligence: A survey among members of the AGA Society for Arthroscopy and Joint Surgery

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          Abstract

          Purpose

          The purpose of this study was to evaluate the perspective of orthopaedic surgeons on the impact of artificial intelligence (AI) and to evaluate the influence of experience, workplace setting and familiarity with digital solutions on views on AI.

          Methods

          Orthopaedic surgeons of the AGA Society for Arthroscopy and Joint Surgery were invited to participate in an online, cross‐sectional survey designed to gather information on professional background, subjective AI knowledge, opinion on the future impact of AI, openness towards different applications of AI, and perceived advantages and disadvantages of AI. Subgroup analyses were performed to examine the influence of experience, workplace setting and openness towards digital solutions on perspectives towards AI.

          Results

          Overall, 360 orthopaedic surgeons participated. The majority indicated average (43.6%) or rudimentary (38.1%) AI knowledge. Most (54.5%) expected AI to substantially influence orthopaedics within 5–10 years, predominantly as a complementary tool (91.1%). Preoperative planning (83.8%) was identified as the most likely clinical use case. A lack of consensus was observed regarding acceptable error levels. Time savings in preoperative planning (62.5%) and improved documentation (81%) were identified as notable advantages while declining skills of the next generation (64.5%) were rated as the most substantial drawback. There were significant differences in subjective AI knowledge depending on participants' experience ( p = 0.021) and familiarity with digital solutions ( p < 0.001), acceptable error levels depending on workplace setting ( p = 0.004), and prediction of AI impact depending on familiarity with digital solutions ( p < 0.001).

          Conclusion

          The majority of orthopaedic surgeons in this survey anticipated a notable positive impact of AI on their field, primarily as an assistive technology. A lack of consensus on acceptable error levels of AI and concerns about declining skills among future surgeons were observed.

          Level of Evidence

          Level IV, cross‐sectional study.

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          Most cited references51

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          The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database

          At the beginning of the artificial intelligence (AI)/machine learning (ML) era, the expectations are high, and experts foresee that AI/ML shows potential for diagnosing, managing and treating a wide variety of medical conditions. However, the obstacles for implementation of AI/ML in daily clinical practice are numerous, especially regarding the regulation of these technologies. Therefore, we provide an insight into the currently available AI/ML-based medical devices and algorithms that have been approved by the US Food & Drugs Administration (FDA). We aimed to raise awareness of the importance of regulatory bodies, clearly stating whether a medical device is AI/ML based or not. Cross-checking and validating all approvals, we identified 64 AI/ML based, FDA approved medical devices and algorithms. Out of those, only 29 (45%) mentioned any AI/ML-related expressions in the official FDA announcement. The majority (85.9%) was approved by the FDA with a 510(k) clearance, while 8 (12.5%) received de novo pathway clearance and one (1.6%) premarket approval (PMA) clearance. Most of these technologies, notably 30 (46.9%), 16 (25.0%), and 10 (15.6%) were developed for the fields of Radiology, Cardiology and Internal Medicine/General Practice respectively. We have launched the first comprehensive and open access database of strictly AI/ML-based medical technologies that have been approved by the FDA. The database will be constantly updated.
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            Artificial Intelligence in Surgery

            The aim of this review was to summarize major topics in artificial intelligence (AI), including their applications and limitations in surgery. This paper reviews the key capabilities of AI to help surgeons understand and critically evaluate new AI applications and to contribute to new developments.
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              Physician Confidence in Artificial Intelligence: An Online Mobile Survey

              Background It is expected that artificial intelligence (AI) will be used extensively in the medical field in the future. Objective The purpose of this study is to investigate the awareness of AI among Korean doctors and to assess physicians’ attitudes toward the medical application of AI. Methods We conducted an online survey composed of 11 closed-ended questions using Google Forms. The survey consisted of questions regarding the recognition of and attitudes toward AI, the development direction of AI in medicine, and the possible risks of using AI in the medical field. Results A total of 669 participants completed the survey. Only 40 (5.9%) answered that they had good familiarity with AI. However, most participants considered AI useful in the medical field (558/669, 83.4% agreement). The advantage of using AI was seen as the ability to analyze vast amounts of high-quality, clinically relevant data in real time. Respondents agreed that the area of medicine in which AI would be most useful is disease diagnosis (558/669, 83.4% agreement). One possible problem cited by the participants was that AI would not be able to assist in unexpected situations owing to inadequate information (196/669, 29.3%). Less than half of the participants(294/669, 43.9%) agreed that AI is diagnostically superior to human doctors. Only 237 (35.4%) answered that they agreed that AI could replace them in their jobs. Conclusions This study suggests that Korean doctors and medical students have favorable attitudes toward AI in the medical field. The majority of physicians surveyed believed that AI will not replace their roles in the future.
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                Author and article information

                Contributors
                marco.rupp@tum.de
                Journal
                J Exp Orthop
                J Exp Orthop
                10.1002/(ISSN)2197-1153
                JEO2
                Journal of Experimental Orthopaedics
                John Wiley and Sons Inc. (Hoboken )
                2197-1153
                06 July 2024
                July 2024
                : 11
                : 3 ( doiID: 10.1002/jeo2.v11.3 )
                : e12080
                Affiliations
                [ 1 ] Sektion Sportorthopädie, Klinikum rechts der Isar Technische Universität München Munich Germany
                [ 2 ] Steadman Philippon Research Institute Vail Colorado USA
                [ 3 ] Klinische Abteilung für Orthopädie und Traumatologie Universitätsklinikum Krems Krems an der Donau Austria
                [ 4 ] Zentrum für Regenerative Medizin Universität für Weiterbildung Krems Krems an der Donau Austria
                [ 5 ] Sporthopaedicum Regensburg Germany
                [ 6 ] Universitätsklinik für Orthopädische Chirurgie und Traumatologie, Inselspital Bern Switzerland
                [ 7 ] Klinik für Unfall‐ und Wiederherstellungschirurgie Universitätsklinikum Regensburg Regensburg Germany
                [ 8 ] Universitätsklinikum Halle (Saale) Halle Germany
                [ 9 ] Gelenkzentrum Leipzig Leipzig Germany
                [ 10 ] Fakultät für Gesundheit und Medizin Universität für Weiterbildung Krems Krems an der Donau Austria
                [ 11 ] Klinik für Orthopädie und Unfallchirurgie, Universitätsklinikum Freiburg, Medizinische Fakultät Albert‐Ludwigs‐Universität Freiburg Freiburg Germany
                [ 12 ] OCM – Orthopädische Chirurgie München Munich Germany
                [ 13 ] Albert‐Ludwigs‐University Freiburg Germany
                Author notes
                [*] [* ] Correspondence Marco‐Christopher Rupp, Sektion Sportorthopädie, Technische Universität München, Klinikum rechts der Isar, Ismaninger Str. 22, München 81675, Germany.

                Email: marco.rupp@ 123456tum.de

                Author information
                http://orcid.org/0000-0001-7899-6299
                http://orcid.org/0009-0001-4128-5431
                Article
                JEO212080
                10.1002/jeo2.12080
                11227606
                38974054
                b52641f3-6eed-4dd1-8835-2fc9702c60bd
                © 2024 The Author(s). Journal of Experimental Orthopaedics published by John Wiley & Sons Ltd on behalf of European Society of Sports Traumatology, Knee Surgery and Arthroscopy.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 13 June 2024
                : 02 May 2024
                : 21 June 2024
                Page count
                Figures: 5, Tables: 2, Pages: 10, Words: 5946
                Categories
                Original Paper
                Original Paper
                Custom metadata
                2.0
                July 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.5 mode:remove_FC converted:07.07.2024

                artificial intelligence,attitude of health personnel,machine learning,orthopaedics,survey

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