This paper is in the following e-collection/theme issue:

Clinical Information and Decision Making (1656) Research Instruments, Questionnaires, and Tools (665) Insomnia and Sleep Hygiene (208) Machine Learning (1738) New Methods (1030) Sleep Apnea (33) Sleep Monitoring, Sleep Quality, Sleep Disorders (227) mHealth for Diagnosis (69)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51615, first published .
Efficient Screening in Obstructive Sleep Apnea Using Sequential Machine Learning Models, Questionnaires, and Pulse Oximetry Signals: Mixed Methods Study

Efficient Screening in Obstructive Sleep Apnea Using Sequential Machine Learning Models, Questionnaires, and Pulse Oximetry Signals: Mixed Methods Study

Efficient Screening in Obstructive Sleep Apnea Using Sequential Machine Learning Models, Questionnaires, and Pulse Oximetry Signals: Mixed Methods Study

Authors of this article:

Nai-Yu Kuo1, 2, 3 Author Orcid Image ;   Hsin-Jung Tsai2 Author Orcid Image ;   Shih-Jen Tsai2, 3 Author Orcid Image ;   Albert C Yang1, 2, 4, 5 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Nai-Yu Kuo   1, 2, 3 , MS ;   Hsin-Jung Tsai   2 , PhD ;   Shih-Jen Tsai   2, 3 , MD ;   Albert C Yang   1, 2, 4, 5 , MD, PhD

1 Sleep Medicine Center, Taipei Veterans General Hospital, Taipei, Taiwan

2 Institute of Brain Science, National YangMing Chiao Tung University, Taipei, Taiwan

3 Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan

4 Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan

5 Digital Medicine and Smart Healthcare Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan

Corresponding Author:

  • Albert C Yang, MD, PhD
  • Digital Medicine and Smart Healthcare Research Center
  • National Yang Ming Chiao Tung University
  • No 155 Sec 2 Linong Street
  • Beitou Dist
  • Taipei, 11221
  • Taiwan
  • Phone: 886 02-28267000 ext 66555
  • Email: accyang@gmail.com