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Vibhuarvind / Detection-of-Depression-Using-Late-Fusion-of-Sequential-Actigraphy-Features

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Analyzed time-series data (Depressjon) to detect depression from patient activity recorded via clinical actigraphy watches. Utilized features such as time domain, statistical metrics, and LSTM-extracted attributes.

lstm statistical-inference adaboost sleep-tracker svc time-series-analysis behavioural timedomain depression-detection featurefusion stacking-classifier votingcl latefusion
  • Updated Jun 30, 2024
  • Jupyter Notebook

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