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Artificial intelligence in sleep medicine: background and implications for clinicians

The most immediate application of AI in sleep medicine,

analysis of multiple physiological signals acquired during PSG,

is expected to deepen our understanding of the architecture of

normal and disturbed sleep, improve disease sub-typing, and

increase efficiency of sleep laboratory operations to improve

patient care. However, no singular objective assessment can

replace comprehensive clinical appraisal. AI analyses must be

used in conjunction with careful assessment of patient signs and

symptoms, demographics and comorbidities, and reassessment over the course of the chronic conditions we treat. Like any diagnostic tool, AI will be dependent on the clinician’s aptitude and the context in which it is incorporated in order to achieve

clinical utility.


AI in sleep medicine background and implications for clinicians
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