Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study.

Journal: American journal of otolaryngology
PMID:

Abstract

OBJECTIVE: To develop a multi-instance learning (MIL) based artificial intelligence (AI)-assisted diagnosis models by using laryngoscopic images to differentiate benign and malignant vocal fold leukoplakia (VFL).

Authors

  • Mei-Ling Wang
    Department of Endoscopy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
  • Cheng-Wei Tie
    Department of Endoscopy, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Jian-Hui Wang
    College of Information Science and Engineering, Northeastern University, Shenyang 110004, China.
  • Ji-Qing Zhu
    Department of Endoscopy, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Bing-Hong Chen
    Department of Endoscopy, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Shenzhen, China.
  • Ying Li
    School of Information Engineering, Chang'an University, Xi'an 710010, China.
  • Sen Zhang
    Department of Gastrointestinal Surgery, Hernia Center, West China Hospital, Sichuan University, Chengdu, China.
  • Lin Liu
    Institute of Natural Sciences, MOE-LSC, School of Mathematical Sciences, CMA-Shanghai, SJTU-Yale Joint Center for Biostatistics and Data Science, Shanghai Jiao Tong University; Shanghai Artificial Intelligence Laboratory.
  • Li Guo
    Department of Dental Implantology, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Institute of Stomatology, Nanjing University, Nanjing, China.
  • Long Yang
    Department of Otolaryngology, The Second People's Hospital of Baoshan City, Baoshan, China.
  • Li-Qun Yang
    Department of Otolaryngology, The Second People's Hospital of Baoshan City, Baoshan, China.
  • Jiao Wei
    Department of Otolaryngology, Qujing Second People's Hospital of Yunnan Province, Qujing, China.
  • Feng Jiang
    Hospital of Minzu University of China, Beijing 100081, China.
  • Zhi-Qiang Zhao
    Department of Otolaryngology, Baoshan People's Hospital, Baoshan, China.
  • Gui-Qi Wang
    Department of Endoscopy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. Electronic address: wangguiq@126.com.
  • Wei Zhang
    The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Quan-Mao Zhang
    Department of Endoscopy, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China. Electronic address: zhangqm202203@163.com.
  • Xiao-Guang Ni
    Department of Endoscopy, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.