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

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.

Primary LanguageJupyter NotebookMIT LicenseMIT

No issues in this repository yet.