Comparison of Neural Networks for Prediction of Sleep Apnea

Yashar Maali, Adel Al-Jumaily


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%.


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Paper Citation

in Harvard Style

Maali Y. and Al-Jumaily A. (2013). Comparison of Neural Networks for Prediction of Sleep Apnea . In Proceedings of the International Congress on Neurotechnology, Electronics and Informatics - Volume 1: NEUROTECHNIX, ISBN 978-989-8565-80-8, pages 60-64. DOI: 10.5220/0004701400600064

in Bibtex Style

author={Yashar Maali and Adel Al-Jumaily},
title={Comparison of Neural Networks for Prediction of Sleep Apnea},
booktitle={Proceedings of the International Congress on Neurotechnology, Electronics and Informatics - Volume 1: NEUROTECHNIX,},

in EndNote Style

JO - Proceedings of the International Congress on Neurotechnology, Electronics and Informatics - Volume 1: NEUROTECHNIX,
TI - Comparison of Neural Networks for Prediction of Sleep Apnea
SN - 978-989-8565-80-8
AU - Maali Y.
AU - Al-Jumaily A.
PY - 2013
SP - 60
EP - 64
DO - 10.5220/0004701400600064