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.
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