Detecting obstructive sleep apnea by craniofacial image-based deep learning.

Journal: Sleep & breathing = Schlaf & Atmung
Published Date: Feb 7, 2022

Abstract

STUDY OBJECTIVES: This study aimed to develop a deep learning-based model to detect obstructive sleep apnea (OSA) using craniofacial photographs.

Authors

  • Shuai He
    Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, 1 Dongjiaominxiang, Dongcheng District, Beijing, 100730, People's Republic of China.
  • Hang Su
    Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Yanru Li
    Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China.
  • Wen Xu
    Xiangyang Central HospitalAffiliated Hospital of Hubei University of Arts and Science Xiangyang 441000 China.
  • Xingjun Wang
    Department of Electronic Engineering, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China. wangxingjun@tsinghua.edu.cn.
  • Demin Han
    Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China. deminhan_ent@hotmail.com.

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