Artificial intelligence in orthopedics: fundamentals, current applications, and future perspectives
Abstract Conventional diagnostic and therapeutic approaches in orthopedics are frequently time intensive and associated with elevated rates of diagnostic error, underscoring the urgent need for more efficient tools to improve the current situation. Recently, artificial intelligence (AI) has been inc...
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| Format: | Article |
| Language: | English |
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BMC
2025-08-01
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| Series: | Military Medical Research |
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| Online Access: | https://doi.org/10.1186/s40779-025-00633-z |
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| author | Jian Song Guang-Chao Wang Si-Cheng Wang Chong-Ru He Ying-Ze Zhang Xiao Chen Jia-Can Su |
| author_facet | Jian Song Guang-Chao Wang Si-Cheng Wang Chong-Ru He Ying-Ze Zhang Xiao Chen Jia-Can Su |
| author_sort | Jian Song |
| collection | DOAJ |
| description | Abstract Conventional diagnostic and therapeutic approaches in orthopedics are frequently time intensive and associated with elevated rates of diagnostic error, underscoring the urgent need for more efficient tools to improve the current situation. Recently, artificial intelligence (AI) has been increasingly integrated into orthopedic practice, providing data-driven approaches to support diagnostic and therapeutic processes. With the continuous advancement of AI technologies and their incorporation into routine orthopedic workflows, a comprehensive understanding of AI principles and their clinical applications has become increasingly essential. The review commences with a summary of the core concepts and historical evolution of AI, followed by an examination of machine learning and deep learning frameworks designed for orthopedic clinical and research applications. We then explore various AI-based applications in orthopedics, including image analysis, disease diagnosis, and treatment approaches such as surgical assistance, drug development, rehabilitation support, and personalized therapy. These applications are designed to help researchers and clinicians gain a deeper understanding of the current applications of AI in orthopedics. The review also highlights key challenges and limitations that affect the practical use of AI, such as data quality, model generalizability, and clinical validation. Finally, we discuss possible future directions for improving AI technologies and promoting their safe and effective integration into orthopedic care. |
| format | Article |
| id | doaj-art-1e40678f9e0a4229903ef619f6c79c8d |
| institution | Kabale University |
| issn | 2054-9369 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | BMC |
| record_format | Article |
| series | Military Medical Research |
| spelling | doaj-art-1e40678f9e0a4229903ef619f6c79c8d2025-08-20T04:01:53ZengBMCMilitary Medical Research2054-93692025-08-0112112010.1186/s40779-025-00633-zArtificial intelligence in orthopedics: fundamentals, current applications, and future perspectivesJian Song0Guang-Chao Wang1Si-Cheng Wang2Chong-Ru He3Ying-Ze Zhang4Xiao Chen5Jia-Can Su6Department of Orthopedics, Trauma Orthopedics Center, Institute of Musculoskeletal Injury and Translational Medicine of Organoids, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of MedicineDepartment of Orthopedics, Trauma Orthopedics Center, Institute of Musculoskeletal Injury and Translational Medicine of Organoids, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of MedicineDepartment of Orthopedics, Shanghai Zhongye HospitalDepartment of Orthopedics, Trauma Orthopedics Center, Institute of Musculoskeletal Injury and Translational Medicine of Organoids, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of MedicineDepartment of Orthopedics, Orthopedic Research Institution of Hebei Province, NHC Key Laboratory of Intelligent Orthopedic Equipment, The Third Hospital of Hebei Medical UniversityDepartment of Orthopedics, Trauma Orthopedics Center, Institute of Musculoskeletal Injury and Translational Medicine of Organoids, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of MedicineDepartment of Orthopedics, Trauma Orthopedics Center, Institute of Musculoskeletal Injury and Translational Medicine of Organoids, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of MedicineAbstract Conventional diagnostic and therapeutic approaches in orthopedics are frequently time intensive and associated with elevated rates of diagnostic error, underscoring the urgent need for more efficient tools to improve the current situation. Recently, artificial intelligence (AI) has been increasingly integrated into orthopedic practice, providing data-driven approaches to support diagnostic and therapeutic processes. With the continuous advancement of AI technologies and their incorporation into routine orthopedic workflows, a comprehensive understanding of AI principles and their clinical applications has become increasingly essential. The review commences with a summary of the core concepts and historical evolution of AI, followed by an examination of machine learning and deep learning frameworks designed for orthopedic clinical and research applications. We then explore various AI-based applications in orthopedics, including image analysis, disease diagnosis, and treatment approaches such as surgical assistance, drug development, rehabilitation support, and personalized therapy. These applications are designed to help researchers and clinicians gain a deeper understanding of the current applications of AI in orthopedics. The review also highlights key challenges and limitations that affect the practical use of AI, such as data quality, model generalizability, and clinical validation. Finally, we discuss possible future directions for improving AI technologies and promoting their safe and effective integration into orthopedic care.https://doi.org/10.1186/s40779-025-00633-zArtificial intelligence (AI)OrthopedicsMachine learning (ML)Deep learning (DL)DiagnosticTherapeutics |
| spellingShingle | Jian Song Guang-Chao Wang Si-Cheng Wang Chong-Ru He Ying-Ze Zhang Xiao Chen Jia-Can Su Artificial intelligence in orthopedics: fundamentals, current applications, and future perspectives Military Medical Research Artificial intelligence (AI) Orthopedics Machine learning (ML) Deep learning (DL) Diagnostic Therapeutics |
| title | Artificial intelligence in orthopedics: fundamentals, current applications, and future perspectives |
| title_full | Artificial intelligence in orthopedics: fundamentals, current applications, and future perspectives |
| title_fullStr | Artificial intelligence in orthopedics: fundamentals, current applications, and future perspectives |
| title_full_unstemmed | Artificial intelligence in orthopedics: fundamentals, current applications, and future perspectives |
| title_short | Artificial intelligence in orthopedics: fundamentals, current applications, and future perspectives |
| title_sort | artificial intelligence in orthopedics fundamentals current applications and future perspectives |
| topic | Artificial intelligence (AI) Orthopedics Machine learning (ML) Deep learning (DL) Diagnostic Therapeutics |
| url | https://doi.org/10.1186/s40779-025-00633-z |
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