Predicting Obstructive Sleep Apnea Based on Computed Tomography Scans Using Deep Learning Models-Reference-Cited by-同舟云学术

Predicting Obstructive Sleep Apnea Based on Computed Tomography Scans Using Deep Learning Models

Published:2024-07-15 Issue:2 Volume:210 Page:211-221
ISSN:1073-449X
Container-title:American Journal of Respiratory and Critical Care Medicine
language:en
Short-container-title:Am J Respir Crit Care Med

Author:

Kim Jeong-Whun¹,Lee Kyungsu²,Kim Hyun Jik³,Park Hae Chan¹,Hwang Jae Youn²,Park Seok-Won⁴,Kong Hyoun-Joong⁵⁶⁷,Kim Jin Youp⁸⁴^ORCID

Affiliation:

1. Department of Otorhinolaryngology–Head and Neck Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea;

2. Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea;

3. Department of Otorhinolaryngology–Head and Neck Surgery,

4. Department of Otorhinolaryngology–Head and Neck Surgery, Ilsan Hospital, Dongguk University, Gyeonggi, Republic of Korea

5. Department of Transdisciplinary Medicine,

6. Innovative Medical Technology Research Institute, Seoul National University Hospital, Seoul, Republic of Korea,

7. Department of Medicine, and

8. Interdisciplinary Program of Medical Informatics, Seoul National University College of Medicine, Seoul, Republic of Korea; and

Funder

National Research Foundation of Korea

Publisher

American Thoracic Society

Link

https://www.atsjournals.org/doi/pdf/10.1164/rccm.202304-0767OC

Reference30 articles.

1. Prevalence of obstructive sleep apnea in the general population: A systematic review

2. Excessive Daytime Sleepiness at Work and Subjective Work Performance in the General Population and Among Heavy Snorers and Patients With Obstructive Sleep Apnea

3. Depression, physical activity, energy consumption, and quality of life in OSA patients before and after CPAP treatment

4. Sleep-disordered Breathing and Cardiovascular Disease

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1. We Can Use Machine Learning to Predict Obstructive Sleep Apnea;American Journal of Respiratory and Critical Care Medicine;2024-07-15