YOLOX-SwinT algorithm improves the accuracy of AO/OTA classification of intertrochanteric fractures by orthopedic trauma surgeons.

Journal: Chinese journal of traumatology = Zhonghua chuang shang za zhi
Published Date: Jan 1, 2025

Abstract

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification.

Authors

  • Xue-Si Liu
    Department of Medical Engineering, Daping Hospital, Army Medical University, Chongqing, 400042, China.
  • Rui Nie
    Chinese Flight Test Establishment, Xi'an, China.
  • Ao-Wen Duan
    Department of Medical Engineering, Daping Hospital, Army Medical University, Chongqing, 400042, China.
  • Li Yang
    Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
  • Xiang Li
    Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
  • Le-Tian Zhang
    Department of Radiology, Daping Hospital, Army Medical University, Chongqing, 400042, China.
  • Guang-Kuo Guo
    Department of Radiology, Daping Hospital, Army Medical University, Chongqing, 400042, China.
  • Qing-Shan Guo
    Division of Trauma and War Injury, Daping Hospital, Army Medical University of PLA, State Key Laboratory of Trauma and Chemical Poisoning, Chongqing, 400042, China.
  • Dong-Chu Zhao
    Division of Trauma and War Injury, Daping Hospital, Army Medical University of PLA, State Key Laboratory of Trauma and Chemical Poisoning, Chongqing, 400042, China.
  • Yang Li
    Occupation of Chinese Center for Disease Control and Prevention, Beijing, China.
  • He-Hua Zhang
    Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.

Keywords

External Resources

Popular Topics
Recent Journals