Exploring artificial intelligence in orthopaedics: A collaborative survey from the ISAKOS Young Professional Task Force
Abstract Purpose Through an analysis of findings from a survey about the use of artificial intelligence (AI) in orthopaedics, the aim of this study was to establish a scholarly foundation for the discourse on AI in orthopaedics and to elucidate key patterns, challenges and potential future trajector...
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Journal of Experimental Orthopaedics |
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| Online Access: | https://doi.org/10.1002/jeo2.70181 |
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| author | Filippo Familiari Adnan Saithna Juan Pablo Martinez‐Cano Jorge Chahla Juan Miguel Del Castillo Nicholas N. DePhillipo Gilbert Moatshe Edoardo Monaco Jaime Palos Lucio Pieter D'Hooghe Robert F. LaPrade the ISAKOS Young Professionals Task Force |
| author_facet | Filippo Familiari Adnan Saithna Juan Pablo Martinez‐Cano Jorge Chahla Juan Miguel Del Castillo Nicholas N. DePhillipo Gilbert Moatshe Edoardo Monaco Jaime Palos Lucio Pieter D'Hooghe Robert F. LaPrade the ISAKOS Young Professionals Task Force |
| author_sort | Filippo Familiari |
| collection | DOAJ |
| description | Abstract Purpose Through an analysis of findings from a survey about the use of artificial intelligence (AI) in orthopaedics, the aim of this study was to establish a scholarly foundation for the discourse on AI in orthopaedics and to elucidate key patterns, challenges and potential future trajectories for AI applications within the field. Methods The International Society of Arthroscopy, Knee Surgery and Orthopaedic Sports Medicine (ISAKOS) Young Professionals Task Force developed a survey to collect feedback on issues related to the use of AI in the orthopaedic field. The survey included 26 questions. Data obtained from the completed questionnaires were transferred to a spreadsheet and then analyzed. Results Two hundred and eleven orthopaedic surgeons completed the survey. The survey encompassed responses from a diverse cohort of orthopaedic professionals, predominantly comprising males (92.9%). There was wide representation across all geographic regions. A notable proportion (52.1%) reported uncertainty or lack of differentiation among AI, machine learning and deep learning (47.9%). Respondents identified imaging‐based diagnosis (60.2%) as the primary field of orthopaedics poised to benefit from AI. A considerable proportion (25.1%) reported using AI in their practice, with primary reasons including referencing scientific literature/publications (40.3%). The vast majority expressed interest in leveraging AI technologies (95.3%), demonstrating an inclination towards incorporating AI into orthopaedic practice. Respondents indicated specific areas of interest for further study, including prediction of patient outcomes after surgery (30.8%) and image‐based diagnosis of osteoarthritis (28%). Conclusions This survey demonstrates that there is currently limited use of AI in orthopaedic practice, mainly due to a lack of knowledge about the subject, a lack of proven evidence of its real utility and high costs. These findings are in accordance with other surveys in the literature. However, there is also a high level of interest in its use in the future, in increased study and further research on the subject, so that it can be of real benefit and make AI an integral part of the orthopaedic surgeon's daily work. Level of Evidence Level IV, survey study. |
| format | Article |
| id | doaj-art-5db880dc1e8a443cbada0d45936eed17 |
| institution | Kabale University |
| issn | 2197-1153 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Experimental Orthopaedics |
| spelling | doaj-art-5db880dc1e8a443cbada0d45936eed172025-08-20T03:47:36ZengWileyJournal of Experimental Orthopaedics2197-11532025-01-01121n/an/a10.1002/jeo2.70181Exploring artificial intelligence in orthopaedics: A collaborative survey from the ISAKOS Young Professional Task ForceFilippo Familiari0Adnan Saithna1Juan Pablo Martinez‐Cano2Jorge Chahla3Juan Miguel Del Castillo4Nicholas N. DePhillipo5Gilbert Moatshe6Edoardo Monaco7Jaime Palos Lucio8Pieter D'Hooghe9Robert F. LaPrade10the ISAKOS Young Professionals Task ForceDepartment of Orthopaedic and Trauma Surgery Magna Graecia University Catanzaro ItalyDepartment of Orthopedic Surgery University of Arizona Tucson Arizona USADepartamento de Ortopedia Fundación Valle del Lili Cali ColombiaDepartment of Orthopaedic Surgery Rush University Medical Center Chicago Illinois USAClínica de Traumatología y Ortopedia Universidad de la República Montevideo UruguayDepartment of Orthopedics University of Pennsylvania Philadelphia Pennsylvania USAOslo Sports Trauma Research Center Norwegian School of Sports Science Oslo NorwayOrthopaedic Unit University of Rome La Sapienza, Sant'Andrea Hospital Rome ItalyDepartment of Orthopedic Surgery Hospital Central Dr Ignacio Morones Prieto San Luis Potosí MexicoAspetar Orthopaedic and Sports Medicine Hospital Doha QatarTwin Cities Orthopedics Edina Minnesota USAAbstract Purpose Through an analysis of findings from a survey about the use of artificial intelligence (AI) in orthopaedics, the aim of this study was to establish a scholarly foundation for the discourse on AI in orthopaedics and to elucidate key patterns, challenges and potential future trajectories for AI applications within the field. Methods The International Society of Arthroscopy, Knee Surgery and Orthopaedic Sports Medicine (ISAKOS) Young Professionals Task Force developed a survey to collect feedback on issues related to the use of AI in the orthopaedic field. The survey included 26 questions. Data obtained from the completed questionnaires were transferred to a spreadsheet and then analyzed. Results Two hundred and eleven orthopaedic surgeons completed the survey. The survey encompassed responses from a diverse cohort of orthopaedic professionals, predominantly comprising males (92.9%). There was wide representation across all geographic regions. A notable proportion (52.1%) reported uncertainty or lack of differentiation among AI, machine learning and deep learning (47.9%). Respondents identified imaging‐based diagnosis (60.2%) as the primary field of orthopaedics poised to benefit from AI. A considerable proportion (25.1%) reported using AI in their practice, with primary reasons including referencing scientific literature/publications (40.3%). The vast majority expressed interest in leveraging AI technologies (95.3%), demonstrating an inclination towards incorporating AI into orthopaedic practice. Respondents indicated specific areas of interest for further study, including prediction of patient outcomes after surgery (30.8%) and image‐based diagnosis of osteoarthritis (28%). Conclusions This survey demonstrates that there is currently limited use of AI in orthopaedic practice, mainly due to a lack of knowledge about the subject, a lack of proven evidence of its real utility and high costs. These findings are in accordance with other surveys in the literature. However, there is also a high level of interest in its use in the future, in increased study and further research on the subject, so that it can be of real benefit and make AI an integral part of the orthopaedic surgeon's daily work. Level of Evidence Level IV, survey study.https://doi.org/10.1002/jeo2.70181arthroscopyartificial intelligencediagnosisorthopaedicssports medicine |
| spellingShingle | Filippo Familiari Adnan Saithna Juan Pablo Martinez‐Cano Jorge Chahla Juan Miguel Del Castillo Nicholas N. DePhillipo Gilbert Moatshe Edoardo Monaco Jaime Palos Lucio Pieter D'Hooghe Robert F. LaPrade the ISAKOS Young Professionals Task Force Exploring artificial intelligence in orthopaedics: A collaborative survey from the ISAKOS Young Professional Task Force Journal of Experimental Orthopaedics arthroscopy artificial intelligence diagnosis orthopaedics sports medicine |
| title | Exploring artificial intelligence in orthopaedics: A collaborative survey from the ISAKOS Young Professional Task Force |
| title_full | Exploring artificial intelligence in orthopaedics: A collaborative survey from the ISAKOS Young Professional Task Force |
| title_fullStr | Exploring artificial intelligence in orthopaedics: A collaborative survey from the ISAKOS Young Professional Task Force |
| title_full_unstemmed | Exploring artificial intelligence in orthopaedics: A collaborative survey from the ISAKOS Young Professional Task Force |
| title_short | Exploring artificial intelligence in orthopaedics: A collaborative survey from the ISAKOS Young Professional Task Force |
| title_sort | exploring artificial intelligence in orthopaedics a collaborative survey from the isakos young professional task force |
| topic | arthroscopy artificial intelligence diagnosis orthopaedics sports medicine |
| url | https://doi.org/10.1002/jeo2.70181 |
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