Depression level classification using machine learning classifiers based on actigraphy data

HIGHLIGHTS

• who: Based on Actigraphy Data et al. from the Graduate Program in Cognitive Science, University, Seoul, Republic of Korea have published the research work: Depression Level Classification Using Machine Learning Classifiers Based on Actigraphy Data, in the Journal: (JOURNAL)
• what: The results of this study provide novel insights into the relationship between depression and physical activity in terms of both identification of depression and application of INDEX TERMS classification algorithm circadian rhythm depression level machine learning multi-level classification physical activity. The authors proposed a classification framework for depression levels (e_g, ‘mild,' ‘moderate,' or ‘severe . . .
  

   

  

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