A new distal radius fracture classification depending on the specific fragments through machine learning clustering method.

Journal: BMC musculoskeletal disorders
PMID:

Abstract

PURPOSES: The objective of this study was to investigate intra-articular distal radius fractures, aiming to provide a comprehensive analysis of fracture patterns and discuss the corresponding treatment strategies for each pattern.

Authors

  • Yuling Gao
    Orthopedics Department, Affiliated Beijing Chaoyang Hospital of Capital Medical University, Bejing, China.
  • Yanrui Zhao
    Orthopedics Department, Affiliated Beijing Chaoyang Hospital of Capital Medical University, Bejing, China.
  • Yang Liu
    Department of Computer Science, Hong Kong Baptist University, Hong Kong, China.
  • Shan Lei
    Department of Gastroenterology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, China.
  • Hanzhou Wang
    Orthopedics Department, Affiliated Beijing Chaoyang Hospital of Capital Medical University, Bejing, China.
  • Yuerong Lizhu
    Rediology, Affiliated Beijing Tiantan Hospital of Capital Medical University, Beijing, China.
  • Tianchao Lu
    Orthopedics Department, Affiliated Beijing Chaoyang Hospital of Capital Medical University, Bejing, China.
  • Zhexian Cheng
    Preventive Dentistry Department, Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China.
  • Dong Wang
    Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
  • Binzhi Zhao
    Orthopedics Department, Affiliated Beijing Chaoyang Hospital of Capital Medical University, Bejing, China.
  • Ziyi Li
    Emory University, Department of Biostatistics and Bioinformatics, Atlanta, GA 30332, USA.
  • Junlin Zhou
    Department of Radiology, Lanzhou University Second Hospital, 730030 Lanzhou, Gansu, China.