Noninvasive prediction of failure of the conservative treatment in lateral epicondylitis by clinicoradiological features and elbow MRI radiomics based on interpretable machine learning: a multicenter cohort study.

Journal: Journal of orthopaedic surgery and research
Published Date: May 24, 2025

Abstract

OBJECTIVES: To develop and validate an interpretable machine learning model based on clinicoradiological features and radiomic features based on magnetic resonance imaging (MRI) to predict the failure of conservative treatment in lateral epicondylitis (LE).

Authors

  • Jianing Cui
    Department of Radiology, Beijing Jishuitan Hospital, Capital Medical University, Beijing, 100035, China.
  • Ping Wang
    School of Chemistry and Chemical Engineering, Shandong University of Technology, 255049, Zibo, PR China. Electronic address: wangping876@163.com.
  • Xiaodong Zhang
    The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Ping Zhang
    Department of Computer Science and Engineering, The Ohio State University, USA.
  • Yuming Yin
    Department of Radiology, Pomona Valley Hospital Medical Center, Pomona, CA, 91767, USA.
  • Rongjie Bai
    Department of Radiology, Beijing Jishuitan Hospital, Capital Medical University, Beijing, 100035, China. bairongjie@126.com.

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