JSM
Journal of Sleep MedicineJ Sleep Med
2384-2423
2384-2431
Korean Sleep Research Society
10.13078/jsm.200022e
jsm-200022e
Erratum
다양한 머신 러닝 알고리즘을 이용한 폐쇄수면무호흡 진단의 정확도
Diagnostic Accuracy of Different Machine Learning Algorithms for Obstructive Sleep Apnea
KimHyun-Woo
김현우
1
ParkEuihwan
박의환
2
KimDae Jin
김대진
3
MunSue Jean
문수진
4
KimJiyoung
김지영
5
LeeGha-Hyun
이가현
5
ChoJae Wook
조재욱
1
Department of Neurology, Pusan National University Yangsan Hospital, Yangsan, Korea
양산부산대학교병원 신경과학교실
Department of Economics, Hannam University, Daejeon, Korea
한남대학교 경상대학 경제학과
Department of Biomedical Laboratory Science, Kyungbok University, Porcheon, Korea
경복대학교 임상병리학과
Department of Otorhinolaryngology , Pusan National University Yangsan Hospital, Yangsan, Korea
양산부산대학교병원 이비인후과학교실
Department of Neurology, Pusan National University Hospital, Busan, Korea
부산대학교병원 신경과학교실
8
2022
24
6
2022
19
2
95
95
Copyright © 2022 Korean Sleep Research Society
2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
J Sleep Med 2020;17(2):128-137 / https://doi.org/10.13078/jsm.200022
We would like to correct the Acknowledgments as written below.
This study was supported by a 2020 research grant from Pusan National University Yangsan Hospital.