The future of sleep medicine is here: how modern data analytics can help answer age-old questions in sleep medicine

The future of sleep medicine is here: How modern data analytics can help answer age-old questions in sleep medicineArtificial intelligence has experienced exponential growth in a wide range of fields, including sleep medicine.Machine learning allows researchers to process and analyze vast amounts of data to uncover complex patterns that may go unnoticed with traditional methods.Deep learning in particular provides powerful data insights as deep neural networks identify salient features that may not have been previously recognized as important with use of legacy techniques.Traditionally, sleep medicine has relied on the classification of sleep stages through visual inspection of polysomnographic records by trained experts.Traditional sleep scoring and the derived aggregate summary measures, although foundational to the field for decades, is limited by a relatively narrow range of information that can be processed at once and depletes polysomnographic data of complexity, nuance, and value.In contrast, machine learning allows