A Review on the Application of Artificial Intelligence and Deep Learning in the Diagnosis and Management of Sleep Apnea

Sleep apnea is a major sleep disorder characterized by recurrent pauses or reductions in airflow during sleep, leading to significant physical and psychological consequences. The gold standard for diagnosis remains polysomnography (PSG), which, despite its high accuracy, is costly, resource-intensive, and not easily accessible to all patients. Over the past decade, advances in artificial intelligence (AI) and deep learning (DL) have enabled the development of innovative, low-cost, and efficient diagnostic tools for sleep apnea. This review, focusing on studies published between ۲۰۱۹ and ۲۰۲۵, explores algorithms, clinical applications, benefits, limitations, and future directions of AI in sleep apnea detection and management.

کلیدواژه ها:

Sleep apnea ، Artificial intelligence ، Deep learning ، Polysomnography ، Wearables ، SpO۲