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Artificial intelligence in orthopedic trauma: a comprehensive review
1Bahcesehir University School of Medicine, Department of Orthopedics and Traumatology, Turkiye.
Injury
|July 19, 2025
Summary
Artificial intelligence (AI) shows great promise in orthopedic trauma care, with AI systems often matching or exceeding specialist performance in fracture detection and classification. However, challenges in clinical integration and validation need addressing for widespread adoption.
Area of Science:
- Orthopedic Trauma Surgery
- Medical Artificial Intelligence
- Health Informatics
Background:
- Artificial intelligence (AI) is rapidly transforming healthcare, particularly in orthopedic trauma.
- The field has seen exponential growth, with over half of studies published in 2024.
- Deep learning and machine learning methods dominate AI research in this area.
Purpose of the Study:
- To review the current state, applications, and future directions of AI in orthopedic trauma.
- To analyze 217 studies published between 2015 and 2025.
- To evaluate the performance and clinical integration of AI in orthopedic trauma care.
Main Methods:
- Systematic review of 217 studies from 2015-2025.
- Analysis of AI approaches (deep learning, machine learning).
- Categorization of applications (fracture detection, classification, prediction, segmentation) and anatomical sites (hip/femur, spine, wrist).
Main Results:
- AI systems frequently match or exceed specialist performance (sensitivity/specificity >90%) in detection and classification.
- Predictive models show significant improvements over traditional scoring systems (AUC increase 0.10-0.15).
- Limited external (14.5%) and prospective clinical validation (3.2%) were reported.
Conclusions:
- AI demonstrates high accuracy in orthopedic trauma tasks but faces challenges in clinical integration, data standardization, and validation.
- Future research should prioritize multimodal data, transparent algorithms, and rigorous clinical validation.
- AI holds potential to enhance diagnostic accuracy, treatment selection, and patient risk stratification in orthopedic trauma.
