Detecting obstructive sleep apnea by craniofacial image–based deep learning

被引：0
|
作者：
Shuai He
Hang Su
Yanru Li
Wen Xu
Xingjun Wang
Demin Han
机构：
[1] Beijing Tongren Hospital,Department of Otolaryngology Head and Neck Surgery
[2] Capital Medical University,Department of Otolaryngology Head and Neck Surgery
[3] Beijing Chaoyang Hospital,Obstructive Sleep Apnea
[4] Capital Medical University,Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre
[5] Capital Medical University,Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education
[6] Capital Medical University,Department of Electronic Engineering
[7] Tsinghua Shenzhen International Graduate School,undefined
[8] Tsinghua University,undefined
来源：
Sleep and Breathing | 2022年 / 26卷
关键词：
Obstructive sleep apnea; Deep learning; Craniofacial photographs;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：1885 / 1895
页数：10
相关论文
共 50 条
  • [41] Craniofacial abnormalities in Chinese patients with obstructive and positional sleep apnea
    Chang, En-Ting
    Shiao, Guang-Ming
    SLEEP MEDICINE, 2008, 9 (04) : 403 - 410
  • [42] Machine learning for image-based detection of patients with obstructive sleep apnea: an exploratory study
    Satoru Tsuiki
    Takuya Nagaoka
    Tatsuya Fukuda
    Yuki Sakamoto
    Fernanda R. Almeida
    Hideaki Nakayama
    Yuichi Inoue
    Hiroki Enno
    Sleep and Breathing, 2021, 25 : 2297 - 2305
  • [43] Constant Q-Transform-Based Deep Learning Architecture for Detection of Obstructive Sleep Apnea
    Kandukuri, Usha Rani
    Prakash, Allam Jaya
    Patro, Kiran Kumar
    Neelapu, Bala Chakravarthy
    Tadeusiewicz, Ryszard
    Plawiak, Pawel
    INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE, 2023, 33 (03) : 493 - 506
  • [44] Predicting Obstructive Sleep Apnea Based on Computed Tomography Scans Using Deep Learning Models
    Kim, Jeong-Whun
    Lee, Kyungsu
    Kim, Hyun Jik
    Park, Hae Chan
    Hwang, Jae Youn
    Park, Seok-Won
    Kong, Hyoun-Joong
    Kim, Jin Youp
    AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2024, 210 (02) : 211 - 221
  • [45] Machine learning for image-based detection of patients with obstructive sleep apnea: an exploratory study
    Tsuiki, Satoru
    Nagaoka, Takuya
    Fukuda, Tatsuya
    Sakamoto, Yuki
    Almeida, Fernanda R.
    Nakayama, Hideaki
    Inoue, Yuichi
    Enno, Hiroki
    SLEEP AND BREATHING, 2021, 25 (04) : 2297 - 2305
  • [46] A NOVEL MACHINE LEARNING MODEL TO PREDICT OBSTRUCTIVE SLEEP APNEA USING CRANIOFACIAL PHOTOGRAPHY WITH QUESTIONNAIRE
    Kim, Yunsoo
    Park, June-Young
    Jang, Yeji
    Kim, Min Hye
    Ryu, Wi-Sun
    Kim, Jee Hyun
    Shin, Hye-Rim
    Kim, Tae-Joon
    SLEEP, 2024, 47 : A218 - A218
  • [47] Characterization of craniofacial-based clinical phenotypes in children with suspected obstructive sleep apnea
    Fagundes, Nathalia Carolina Fernandes
    Loliencar, Prachi
    MacLean, Joanna E.
    Flores-Mir, Carlos
    Heo, Giseon
    JOURNAL OF CLINICAL SLEEP MEDICINE, 2023, 19 (11): : 1857 - 1865
  • [48] A noninvasive technique for detecting obstructive and central sleep apnea
    Yen, FC
    Behbehani, K
    Lucas, EA
    Burk, JR
    Axe, JR
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 1997, 44 (12) : 1262 - 1268
  • [49] Detecting pediatric obstructive sleep apnea using ECG
    Pu, YC
    Patterson, R
    Bornemann, MC
    PROCEEDINGS OF THE 25TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4: A NEW BEGINNING FOR HUMAN HEALTH, 2003, 25 : 342 - 345
  • [50] Deep learning of sleep apnea-hypopnea events for accurate classification of obstructive sleep apnea and determination of clinical severity
    Yook, Soonhyun
    Kim, Dongyeop
    Gupte, Chaitanya
    Joo, Eun Yeon
    Kim, Hosung
    SLEEP MEDICINE, 2024, 114 : 211 - 219
12345