Negative prognostic factors and clinical improvement prediction modeling for extracorporeal shockwave therapy in calcific shoulder tendinitis using artificial intelligence techniques.

Journal: Journal of shoulder and elbow surgery
Published Date: Jan 19, 2025

Abstract

BACKGROUND: The efficacy of extracorporeal shockwave therapy (ESWT) for treating shoulder calcific tendinitis can be influenced by various prognostic factors. This study aimed to identify prognostic factors associated with the failure of ESWT for symptom relief and to evaluate the predictive capability of the eXtreme Gradient Boosting (XGBoost) algorithm of artificial intelligence techniques in this context.

Authors

  • Wen-Yi Chou
    Ph.D. Program in Biomedical Engineering, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Orthopedic Surgery, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Leisure and Sport Management, Cheng Shiu University, Kaohsiung, Taiwan.
  • Tian-Hsiang Huang
    Center for Big Data Research, Kaohsiung Medical University, No. 100, Shin-Chuan 1st Road, Kaohsiung, 807, Taiwan.
  • Jai-Hong Cheng
    Department of Medical Research, Center for Shockwave Medicine and Tissue Engineering, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan.
  • Yu-Jui Lien
    Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, Taiwan.
  • Wen-Hsien Ho
    Department of Healthcare Administration and Medical Informatics, 38023Kaohsiung Medical University, Kaohsiung 807, Taiwan.
  • Paul Pei-Hsi Chou
    Department of Sports Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan; Division of Sports Medicine, Department of Orthopaedic Surgery, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan; Department of Orthopaedics, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan. Electronic address: arthroscopy.pc@gmail.com.

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