RT info:eu-repo/semantics/bookPart
T1 usefulness of artificial neural networks in the diagnosis and treatment of sleep apnea-hypopnea syndrome
A1 Álvarez González, Daniel
A1 Cerezo Hernández, Ana
A1 López Muñiz, Graciela
A1 Álvaro de Castro, Tania
A1 Ruiz Albi, Tomás
A1 Hornero Sánchez, Roberto
A1 Campo Matias, Félix del
K1 Apnea del sueño
K1 Apnea del sueño
K1 Redes neuronales
K1 3201.99 Otras
AB Sleep apnea-hypopnea syndrome (SAHS) is a chronic and highly prevalent disease considered a major health problem in industrialized countries. The gold standard diagnostic methodology is in-laboratory nocturnal polysomnography (PSG), which is complex, costly, and time consuming. In order to overcome these limitations, novel and simplified diagnostic alternatives are demanded. Sleep scientists carried out an exhaustive research during the last decades focused on the design of automated expert systems derived from artificial intelligence able to help sleep specialists in their daily practice. Among automated pattern recognition techniques, artificial neural networks (ANNs) have demonstrated to be efficient and accurate algorithms in order to implement computer-aided diagnosis systems aimed at assisting physicians in the management of SAHS. In this regard, several applications of ANNs have been developed, such as classification of patients suspected of suffering from SAHS, apnea-hypopnea index (AHI) prediction, detection and quantification of respiratory events, apneic events classification, automated sleep staging and arousal detection, alertness monitoring systems, and airflow pressure optimization in positive airway pressure (PAP) devices to fit patients’ needs. In the present research, current applications of ANNs in the framework of SAHS management are thoroughly reviewed.
SN 978-953-51-3056-7
YR 2017
FD 2017
LK https://uvadoc.uva.es/handle/10324/82994
UL https://uvadoc.uva.es/handle/10324/82994
LA eng
NO Alvarez D, Cerezo-Hernandez A, Lopez-Muniz G, Alvaro-De Castro T, Ruiz-Albi T, Hornero R, et al. Usefulness of Artificial Neural Networks in the Diagnosis and Treatment of Sleep Apnea-Hypopnea Syndrome. En: Sleep Apnea - Recent Updates. 2017
NO Producción Científica
DS UVaDOC
RD 23-feb-2026