Developing Machine Learning-Based Predictive Models for Hallux Valgus Recurrence Based on Measurements From Radiographs.

Journal: Foot & ankle international
PMID: 38872342

Abstract

BACKGROUND: Machine learning (ML) is increasingly used to predict the prognosis of numerous diseases. This retrospective analysis aimed to develop a prediction model using ML algorithms and to identify predictors associated with the recurrence of hallux valgus (HV) following surgery.

Authors

  • Rui Zhao
  • Guobin Wang
    National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides Spraying Technology (NPAAC), College of Engineering, South China Agricultural University, Guangzhou, China.
  • Fengtan Li
    Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China.
  • Jinchan Wang
    Department of Dermatology, Tianjin Medical University General Hospital, Tianjin, China.
  • Yuan Zhang
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Dong Li
    Department of Cardiovascular Medicine, Lanzhou University Second Hospital, 730030 Lanzhou, Gansu, China.
  • Shen Liu
    State Key Laboratory for Manufacturing and Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, PR China.
  • Jie Li
    Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence Application Technology Research Institute, Shenzhen Polytechnic University, Shenzhen, China.
  • Jiajun Song
    Department of Orthopedic Surgery, Tianjin Medical University General Hospital, Tianjin, China.
  • Fangyuan Wei
    Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China.
  • Chenguang Wang
    School of Information and Communication Engineering, North University of China, Taiyuan 030051, People's Republic of China.

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