Diagnosis of carpal tunnel syndrome using deep learning with comparative guidance.

Journal: Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Published Date: Jun 1, 2025

Abstract

OBJECTIVE: This study aims to develop a deep learning model for a robust diagnosis of Carpal Tunnel Syndrome (CTS) based on comparative classification leveraging the ultrasound images of the thenar and hypothenar muscles.

Authors

  • Jungsub Sim
    Department of Computer Science, Korea University, Seoul, Republic of Korea.
  • Sungche Lee
    Department of Physical Medicine & Rehabilitation, Korea University, Seoul, Republic of Korea.
  • Seunghyun Kim
    Department of Biology, University of California San Diego, San Diego, CA, 92093, USA.
  • Seong-Ho Jeong
    Department of Physical Medicine & Rehabilitation, Korea University, Seoul, Republic of Korea.
  • Joonshik Yoon
    Department of Physical Medicine & Rehabilitation, Korea University, Seoul, Republic of Korea. Electronic address: rehab46@korea.ac.kr.
  • Seungjun Baek
    Department of Computer Science, Korea University, Seoul, Republic of Korea. Electronic address: sjbaek@korea.ac.kr.

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