Integration of AI-Assisted in Digital Cervical Cytology Training: A Comparative Study.

Journal: Cytopathology : official journal of the British Society for Clinical Cytology
PMID:

Abstract

OBJECTIVE: This study aimed to investigate the supporting role of artificial intelligence (AI) in digital cervical cytology training.

Authors

  • Yihui Yang
    Department of Anesthesiology, Third Affiliated Hospital of Zunyi Medical University, Guizhou Province, China.
  • Dongyi Xian
    Medical Affairs Department, Betrue AI Lab, Guangzhou 510700, China.
  • Lihua Yu
    From the Departments of Radiology (M.L., LY., J.Z.) and Cardiology (W.Y.), Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 85 Wujin Rd, Shanghai 200080, China; Institute of Diagnostic and Interventional Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China (R.L.); and Shanghai United Imaging Intelligence, Shanghai, China (Z.C., D.W.).
  • Yanqing Kong
    Department of Pathology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, China.
  • Huaisheng Lv
    Department of Pathology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, China.
  • Liujing Huang
    Medical Affairs Department, Guangzhou Betrue Technology Co. Ltd., Guangzhou, China.
  • Kai Liu
    College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China.
  • Hao Zhang
    College of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China.
  • Weiwei Wei
    Technology Center, China Tobacco Hunan Industrial Co., Ltd., Changsha 410014, China.
  • Hongping Tang
    Department of Pathology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, China.