Automatic detection of thyroid nodules with a real-time artificial intelligence system in a real clinical scenario and the associated influencing factors.

Journal: Clinical hemorheology and microcirculation
Published Date: Jan 1, 2024

Abstract

BACKGROUND: At present, most articles mainly focused on the diagnosis of thyroid nodules by using artificial intelligence (AI), and there was little research on the detection performance of AI in thyroid nodules.

Authors

  • Ya-Dan Xu
    Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Yang Tang
    School of Science, Jiangsu University, Zhenjiang, China.
  • Qi Zhang
    Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Zheng-Yong Zhao
    Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Chong-Ke Zhao
    Department of Medical Ultrasound, Shanghai Tenth People's Hospital, Ultrasound Research and Education Institute, Tongji University Cancer Center, Shanghai Engineering Research Center of Ultrasound Diagnosis and Treatment, Tongji University School of Medicine, Shanghai, China.
  • Pei-Li Fan
    Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Yun-Jie Jin
    Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Zheng-Biao Ji
    Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Hong Han
  • Hui-Xiong Xu
    Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.
  • Yi-Lei Shi
    MedAI Technology (Wuxi) Co, Ltd, Wuxi, China.
  • Ben-Hua Xu
    Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Xiao-Long Li
    Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, China.

Keywords

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