Artificial intelligence in orthopaedic trauma
With the exponential growth in data processing capabilities and the progressive intertwining of medicine with industry, artificial intelligence (AI) has gained widespread application in the medical domain. Currently, AI is extensively utilized across various aspects of trauma orthopedics, including...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-09-01
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| Series: | EngMedicine |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2950489924000204 |
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| author | Chuwei Tian Yucheng Gao Chen Rui Shengbo Qin Liu Shi Yunfeng Rui |
| author_facet | Chuwei Tian Yucheng Gao Chen Rui Shengbo Qin Liu Shi Yunfeng Rui |
| author_sort | Chuwei Tian |
| collection | DOAJ |
| description | With the exponential growth in data processing capabilities and the progressive intertwining of medicine with industry, artificial intelligence (AI) has gained widespread application in the medical domain. Currently, AI is extensively utilized across various aspects of trauma orthopedics, including fracture identification, diagnosis and stratification, prevention strategies for falls and fractures, emergency management, and perioperative and prognostic risk assessments. This study delves into the research progress and challenges of AI in orthopedic trauma, including the clinical applications of machine learning, deep learning, and natural language processing. By illuminating these dynamic research avenues, this study aimed to catalyze interdisciplinary collaboration and spur innovation at the intersection of AI and orthopedic trauma, ultimately advancing the frontiers of patient care and clinical practice. |
| format | Article |
| id | doaj-art-7bb9ff3a64ae446c9673512cddf2bce6 |
| institution | Kabale University |
| issn | 2950-4899 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | EngMedicine |
| spelling | doaj-art-7bb9ff3a64ae446c9673512cddf2bce62025-01-11T06:42:27ZengElsevierEngMedicine2950-48992024-09-0112100020Artificial intelligence in orthopaedic traumaChuwei Tian0Yucheng Gao1Chen Rui2Shengbo Qin3Liu Shi4Yunfeng Rui5Department of Orthopaedics, Zhongda Hospital, School of Medicine, Southeast University, NO.87 Ding Jia Qiao, Nanjing, Jiangsu 210009, PR China; Multidisciplinary Team (MDT) for Geriatric Hip Fracture Management, Zhongda Hospital, School of Medicine, Southeast University, Nanjing Jiangsu, PR China; Orthopaedic Trauma Institute (OTI), Southeast University, Nanjing, Jiangsu 210009, PR China; Trauma Center, Zhongda Hospital, Southeast University, Nanjing, Jiangsu 210009, PR China; School of Medicine, Southeast University, NO. 87 Ding Jia Qiao, Nanjing, Jiangsu 210009, PR ChinaDepartment of Orthopaedics, Zhongda Hospital, School of Medicine, Southeast University, NO.87 Ding Jia Qiao, Nanjing, Jiangsu 210009, PR China; Multidisciplinary Team (MDT) for Geriatric Hip Fracture Management, Zhongda Hospital, School of Medicine, Southeast University, Nanjing Jiangsu, PR China; Orthopaedic Trauma Institute (OTI), Southeast University, Nanjing, Jiangsu 210009, PR China; Trauma Center, Zhongda Hospital, Southeast University, Nanjing, Jiangsu 210009, PR China; School of Medicine, Southeast University, NO. 87 Ding Jia Qiao, Nanjing, Jiangsu 210009, PR ChinaDepartment of Orthopaedics, Zhongda Hospital, School of Medicine, Southeast University, NO.87 Ding Jia Qiao, Nanjing, Jiangsu 210009, PR China; Multidisciplinary Team (MDT) for Geriatric Hip Fracture Management, Zhongda Hospital, School of Medicine, Southeast University, Nanjing Jiangsu, PR China; Orthopaedic Trauma Institute (OTI), Southeast University, Nanjing, Jiangsu 210009, PR China; Trauma Center, Zhongda Hospital, Southeast University, Nanjing, Jiangsu 210009, PR China; School of Medicine, Southeast University, NO. 87 Ding Jia Qiao, Nanjing, Jiangsu 210009, PR ChinaSchool of Medicine, Southeast University, NO. 87 Ding Jia Qiao, Nanjing, Jiangsu 210009, PR ChinaDepartment of Orthopaedics, Zhongda Hospital, School of Medicine, Southeast University, NO.87 Ding Jia Qiao, Nanjing, Jiangsu 210009, PR China; Multidisciplinary Team (MDT) for Geriatric Hip Fracture Management, Zhongda Hospital, School of Medicine, Southeast University, Nanjing Jiangsu, PR China; Orthopaedic Trauma Institute (OTI), Southeast University, Nanjing, Jiangsu 210009, PR China; Trauma Center, Zhongda Hospital, Southeast University, Nanjing, Jiangsu 210009, PR China; School of Medicine, Southeast University, NO. 87 Ding Jia Qiao, Nanjing, Jiangsu 210009, PR ChinaDepartment of Orthopaedics, Zhongda Hospital, School of Medicine, Southeast University, NO.87 Ding Jia Qiao, Nanjing, Jiangsu 210009, PR China; Multidisciplinary Team (MDT) for Geriatric Hip Fracture Management, Zhongda Hospital, School of Medicine, Southeast University, Nanjing Jiangsu, PR China; Orthopaedic Trauma Institute (OTI), Southeast University, Nanjing, Jiangsu 210009, PR China; Trauma Center, Zhongda Hospital, Southeast University, Nanjing, Jiangsu 210009, PR China; School of Medicine, Southeast University, NO. 87 Ding Jia Qiao, Nanjing, Jiangsu 210009, PR China; Corresponding author. Department of Orthopaedics, Zhongda Hospital, School of Medicine, Southeast University, No. 87 Ding Jia Qiao, Nanjing, Jiangsu 210009, PR China.With the exponential growth in data processing capabilities and the progressive intertwining of medicine with industry, artificial intelligence (AI) has gained widespread application in the medical domain. Currently, AI is extensively utilized across various aspects of trauma orthopedics, including fracture identification, diagnosis and stratification, prevention strategies for falls and fractures, emergency management, and perioperative and prognostic risk assessments. This study delves into the research progress and challenges of AI in orthopedic trauma, including the clinical applications of machine learning, deep learning, and natural language processing. By illuminating these dynamic research avenues, this study aimed to catalyze interdisciplinary collaboration and spur innovation at the intersection of AI and orthopedic trauma, ultimately advancing the frontiers of patient care and clinical practice.http://www.sciencedirect.com/science/article/pii/S2950489924000204Artificial intelligenceMachine learningNatural language processingOrthopedic traumaMedical decision |
| spellingShingle | Chuwei Tian Yucheng Gao Chen Rui Shengbo Qin Liu Shi Yunfeng Rui Artificial intelligence in orthopaedic trauma EngMedicine Artificial intelligence Machine learning Natural language processing Orthopedic trauma Medical decision |
| title | Artificial intelligence in orthopaedic trauma |
| title_full | Artificial intelligence in orthopaedic trauma |
| title_fullStr | Artificial intelligence in orthopaedic trauma |
| title_full_unstemmed | Artificial intelligence in orthopaedic trauma |
| title_short | Artificial intelligence in orthopaedic trauma |
| title_sort | artificial intelligence in orthopaedic trauma |
| topic | Artificial intelligence Machine learning Natural language processing Orthopedic trauma Medical decision |
| url | http://www.sciencedirect.com/science/article/pii/S2950489924000204 |
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