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 ...
First, the data was independently segmented into quintiles (5 levels) for self-relevance and valence based on participant’s ratings. Next, time points (TRs) were assigned according to the levels of ...
Brain–machine interfaces (BMIs) represent a transformative field at the intersection of neuroscience, engineering and computer science, allowing for direct communication between the brain and external ...
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