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| 1.01 MB | Adobe PDF |
Advisor(s)
Abstract(s)
Sleep apnea syndrome (SAS), which can significantly decrease the quality of life is associated with a major risk factor of health implications such as increased cardiovascular disease, sudden death, depression, irritability, hypertension, and learning difficulties. Thus, it is relevant and timely to present a systematic review describing significant applications in the framework of computational intelligence-based SAS, including its performance, beneficial and challenging effects, and modeling for the decision-making on multiple scenarios.
Description
Keywords
Algorithms Humans Polysomnography Sleep Apnea Syndromes Diagnosis Computer-Assisted