A machine learning model can effectively predict a patient’s risk for a sleep disorder using demographic and lifestyle data, physical exam results and laboratory values, according to a new study published this week in the open-access journal PLOS ONE by Samuel Y. Huang of Virginia Commonwealth University School of Medicine, and Alexander A. Huang of Northwestern Feinberg University School of Medicine, U.S.
This article was originally published on MedicalXpress.com
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