Deep learning in the precise assessment of primary Sjögren's syndrome based on ultrasound images.

Journal: Rheumatology (Oxford, England)
PMID: 38830044

Abstract

OBJECTIVES: This study aimed to investigate the value of a deep learning (DL) model based on greyscale ultrasound (US) images for precise assessment and accurate diagnosis of primary Sjögren's syndrome (pSS).

Authors

  • Xinyue Niu
  • Yujie Zhou
    School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China.
  • Jin Xu
    Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, and School of Statistics, East China Normal University, Shanghai, China.
  • Qin Xue
    Department of Ultrasonography, Jiangyin Clinical College of Xuzhou Medical University, Jiangyin, Jiangsu Province, China.
  • Xiaoyan Xu
    School of Control Science and Engineering, Shandong University, Jinan 250061, China.
  • Jia Li
    Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Zhongshan Tsuihang New District, Guangdong, 528400, PR China; School of Pharmacy, Zunyi Medical University, Zunyi, 563000, PR China; National Center for Drug Screening, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, PR China.
  • Ling Wang
    The State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, #7 Jinsui Road, Guangzhou, Guangdong 510230, China.
  • Tianyu Tang
    Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China.

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