![]() One study reviewed the literature on detecting various diseases via computer-aided diagnosis and identified the best machine learning methodology for each disease. There has been considerable research using unsupervised machine learning methodologies in medical sciences not limited to psychiatry. When considering the heterogeneous characteristics of insomnia patients, an approach using precision psychiatry concepts can help develop better treatment methods for insomnia. For instance, unsupervised learning has been applied to distinguish traits of patients with various psychiatric disorders from those of healthy subjects. Advances in machine learning and deep learning techniques can make precision psychiatry possible in clinical situations. With concepts of precision psychiatry emerging, individual characteristics including genetic or neuroimaging, behavioral characteristics, and individual symptoms of illness are being used to make better decisions for diagnosis or treatment. ![]() While an individual’s intermixed behavioral characteristics might affect sleep behaviors, these are not considered in current diagnostic systems such as the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition or the International Classification of Diseases. Work schedule sleep irregularity naps and nicotine, alcohol, and caffeine consumption can have significant effects on insomnia symptoms. Approximately 30% of contemporary people have one or more symptoms of insomnia, and insomnia sufferers encounter difficulty falling or staying asleep. ![]()
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