Development and Validation of an Explainable Machine Learning Model for Identification of Hyper-Functioning Parathyroid Glands from High-Frequency Ultrasonographic Images.

Journal: Ultrasound in medicine & biology
Published Date: Jul 25, 2024

Abstract

OBJECTIVE: To develop and validate a machine learning (ML) model based on high-frequency ultrasound (HFUS) images with the aim to identify the functional status of parathyroid glands (PTGs) in secondary hyper-parathyroidism (SHPT) patients.

Authors

  • Wenwen Zhou
    Department of Medical Ultrasonics, The First Affiliated Hospital, Institute of Diagnostic and Interventional Ultrasound, Sun Yat-Sen University, Guangzhou, China.
  • Yu Zhou
    Department of Biospectroscopy, Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany.
  • Xiaoer Zhang
    Department of Medical Ultrasound, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China.
  • Tongyi Huang
    Department of Medical Ultrasound, Institute for Diagnostic and Interventional Ultrasound, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China.
  • Rui Zhang
    Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Di Li
    Department of Urology, General Hospital of the Air Force, PLA, No. 30 Fucheng Road Haidian District, Beijing, 100142 China.
  • Xiaoyan Xie
    Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, China.
  • Yi Wang
    Department of Neurology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.
  • Ming Xu
    Shenyang Analytical Application Center, Shimadzu (China) Co. Ltd., Shenyang, 167 Qingnian Street, Shenyang, 110016, PR China.

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