Comparison of Neural Networks for Prediction of Sleep Apnea

被引：0

作者：

Maali, Yashar ^{[1
]}

Al-Jumaily, Adel ^{[1
]}

机构：

[1] Univ Technol Sydney, Fac Engn & IT, Ultimo, Australia

来源：

NEUROTECHNIX: PROCEEDINGS OF THE INTERNATIONAL CONGRESS ON NEUROTECHNOLOGY, ELECTRONICS AND INFORMATICS | 2013年

关键词：

Sleep Apnea; Neural Networks; Prediction; DIAGNOSIS; ELECTROCARDIOGRAM; DISORDERS; CRITERIA; ADULTS;

D O I：

10.5220/0004701400600064

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Sleep apnea (SA) is the most important and common component of sleep disorders which has several short term and long term side effects on health. There are several studies on automated SA detection but not too much works have been done on SA prediction. This paper discusses the application of artificial neural net-works (ANNs) to predict sleep apnea. Three types of neural networks were investigated: Elman, cascade-forward and feed-forward back propagation. We assessed the performance of the models using the Receiver Operating Characteristic (ROC) curve, particularly the area under the ROC curves (AUC), and statistically compare the cross validated estimate of the AUC of different models. Based on the obtained results, generally cascade-forward model results are better with average of AUC around 80%.

引用

页码：60 / 64

页数：5

共 50 条

[21] Comparison of features of central sleep apnea and obstructive sleep apnea
Budhiraja, R.
Zeater, M.
Parthasarathy, S.
Quan, S.
SLEEP, 2007, 30 : A158 - A158
[22] An Efficient Prediction of Obstructive Sleep Apnea Using Hybrid Convolutional Neural Network
Rahman, N. Juber
Nithya, P.
FOURTH CONGRESS ON INTELLIGENT SYSTEMS, VOL 1, CIS 2023, 2024, 868 : 297 - 308
[23] A Comparison of Neural Networks for Wireless Channel Prediction
Stenhammar, Oscar
Fodor, Gabor
Fischione, Carlo
IEEE WIRELESS COMMUNICATIONS, 2024, 31 (03) : 235 - 241
[24] Use of Artificial Neural Networks to Predict the Progression of Glaucoma in Patients with Sleep Apnea
Anton, Nicoleta
Lisa, Catalin
Doroftei, Bogdan
Curteanu, Silvia
Bogdanici, Camelia Margareta
Chiselita, Dorin
Branisteanu, Daniel Constantin
Nechita-Dumitriu, Ionela
Ilie, Ovidiu-Dumitru
Ciuntu, Roxana Elena
APPLIED SCIENCES-BASEL, 2022, 12 (12):
[25] A neural prosthesis for obstructive sleep apnea
Yoo, Paul B.
Durand, Dominique M.
2005 27TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7, 2005, : 5254 - 5256
[26] Validity of neural network in sleep apnea
El-Solh, AA
Mador, MJ
Ten-Brock, E
Shucard, DW
Abul-Khoudoud, M
Grant, BJB
SLEEP, 1999, 22 (01) : 105 - 111
[27] Pediatric sleep questionnaire: Prediction of sleep apnea and outcomes
Chervin, Ronald D.
Weatherly, Robert A.
Garetz, Susan L.
Ruzicka, Deborah L.
Giordani, Bruno J.
Hodges, Elise K.
Dillon, James E.
Guire, Kenneth E.
ARCHIVES OF OTOLARYNGOLOGY-HEAD & NECK SURGERY, 2007, 133 (03) : 216 - 222
[28] Automated Apnea-Hypopnea index Estimation By Means Of Neural Networks To Assist In The Diagnosis Of Sleep Apnea In Adults
Crespo, A.
Alvarez, D.
Gutierrez-Tobal, G.
Alvaro De Castro, T.
Arroyo, C.
Hornero, R.
Del Campo, F.
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2016, 193
[29] THE PREDICTION OF OBSTRUCTIVE SLEEP-APNEA
KRAMER, M
SLEEP 88, 1989, : 256 - 257
[30] Characterization of Physiological Networks in Sleep Apnea Patients Using Artificial Neural Networks for Granger Causality Computation
Cardenas, Jhon
Orjuela-Canon, Alvaro D.
Cerquera, Alexander
Ravelo, Antonio
13TH INTERNATIONAL CONFERENCE ON MEDICAL INFORMATION PROCESSING AND ANALYSIS, 2017, 10572

← 1 2 3 4 5 →