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Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study.

Kennedy Opoku AsareYannik TerhorstJulio VegaElla PeltonenEemil LagerspetzDenzil Ferreira
Published in: JMIR mHealth and uHealth (2021)
Our findings demonstrate that behavioral markers indicative of depression can be unobtrusively identified from smartphone sensors' data. Traditional assessment of depression can be augmented with behavioral markers from smartphones for depression diagnosis and monitoring.
Keyphrases
  • depressive symptoms
  • sleep quality
  • machine learning
  • electronic health record
  • physical activity