![]() Therefore, sleep monitoring in both the laboratory and ambulatory environments results in the accrual of massive amounts of data. Additionally, sleep tracking over long durations is ubiquitous given the availability and popularity of fitness trackers and smart watches. Sleep is a physiological state marked by dynamic changes in a variety of organ systems, which is reflected by our use of the polysomnogram, which records various physiological signals across the night. While AI has gained popularity in several fields of medicine including radiology and oncology, the field of sleep medicine stands to greatly benefit from AI. However, there is a need to regulate and standardize existing machine learning algorithms prior to its inclusion in the sleep clinic.ĪI refers to the capability of computer systems to perform tasks conventionally considered to require human intelligence, such as speech recognition, decision-making, and visual recognition of patterns and objects. ConclusionĪrtificial intelligence is a powerful tool in healthcare that may improve patient care, enhance diagnostic abilities, and augment the management of sleep disorders. Overcoming these challenges will help integrate AI seamlessly within sleep medicine and augment clinical practice. ![]() While still in its nascent stage, there are several challenges which preclude AI’s generalizability and wide-reaching clinical applications. ResultsĪrtificial intelligence has several applications in sleep medicine including sleep and respiratory event scoring in the sleep laboratory, diagnosing and managing sleep disorders, and population health. This was supplemented by a thorough review of relevant published literature. The purpose of this article is to provide a concise overview of relevant terminology, definitions, and use cases of AI in sleep medicine. Therefore, sleep monitoring in both the laboratory and ambulatory environments results in the accrual of massive amounts of data that uniquely positions the field of sleep medicine to gain from AI. The practice of sleep tracking and measuring physiological signals in sleep is widely practiced. AI refers to the capability of computer systems to perform tasks conventionally considered to require human intelligence, such as speech recognition, decision-making, and visual recognition of patterns and objects. The past few years have seen a rapid emergence of artificial intelligence (AI)-enabled technology in the field of sleep medicine. ![]()
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