Application of machine learning to predict obstructive sleep apnea syndrome severity.
Corrado MencarCrescenzio GalloMarco ManteroPaolo TarsiaGiovanna E CarpagnanoMaria P Foschino BarbaroDonato LacedoniaPublished in: Health informatics journal (2019)
The problem of predicting apnea-hypopnea index or severity classes for obstructive sleep apnea syndrome is very difficult when using only data collected prior to polysomnography test. The results achieved with the available data suggest the use of machine learning methods as tools for providing patients with a priority level for polysomnography test, but they still cannot be used for automated diagnosis.