A prediction model based on artificial neural networks for the diagnosis of obstructive sleep apnea

Abstract

By establishing a pattern that allows the recognition of OSA, ANNs can be used to identify patients requiring PSG.

Can Statistical Machine Learning Algorithms Help for Classification of Obstructive Sleep Apnea Severity to Optimal Utilization of Polysomno graphy Resources?

“…In recent studies, the need for studies aiming towards clinical prediction for OSA from different settings and countries was also reported [6,7]. In Turkey, only two recent studies which have aimed to detect OSA diagnoses were conducted [11,21]. In one of those studies, Sahin et al used multivariate linear regression analysis to identify independent AHI predictors and derived a formula to predict AHI; and the step wise regression model they used, including the parameters as BMI, neck circumference, waist circumference, peripheral oxygen saturation, and tonsil size, was reached R 2 = 0.682 [21].…”

“…Since there is no widely approved predefined classification of neck circumference, it was categorized in four equally sized groupings using the quintile values of their distribution. A cut-off score of 10 was used for the Epworth sleepiness scale (ESS), with categorization as normal (0-9) and abnormal (10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24) [25].…”

“…Several strategies have been proposed and investigated for the detection of obstructive sleep apnea diagnoses from nonpolysomnographic features to decrease the number of PSG studies [4][5][6][7][8][9][10][11][12][13][14]. In those studies, the clinical features that are associated with the OSA have been combined using statistical modeling or machine learning techniques into a clinical prediction model.…”

Usefulness of Artificial Neural Networks in the Diagnosis and Treatment of Sleep Apnea-Hypopnea Syndrome

“…Indeed, feedforward networks, particularly MLP, are the most popular ANN in the framework of SAHS management [19][20][21]. A particular implementation of MLP networks involving Bayesian inference during the learning process (BY-MLP), which increase the generalization ability and allow for relevance analysis of input variables, has demonstrated to be useful in this context [22].…”

The Use of Artificial Intelligence Methods in the Evaluation of Medical Data

“…It is believed that scientists double the medical knowledge every eight years. We get acquainted with some of the recent technological developments as well as actions with a view to helping to eradicate the disease [7]. Is science able to provide people with satisfactory health condition?…”