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Prediction of Adolescent Depression Relapse Events...
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Prediction of Adolescent Depression Relapse Events Using Fusion of Actigraphy and Ecological Momentary Assessment Features

Abstract

The objective of this study is to explore the application of machine learning (ML) for the prediction of relapse events in adolescents suffering from Major Depressive Disorder using actigraphy and ecological momentary assessment (EMA) data. The data were collected from 114 adolescents aged between 12 and 21 who were participating in a depression research study at the Centre for Addiction and Mental Health. They made up to 8 visits where a …

Authors

Lucasius C; Battaglia M; Strauss J; Szatmari P; Kundur D

Volume

00

Pagination

pp. 448-453

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication Date

October 8, 2023

DOI

10.1109/icccmla58983.2023.10346863

Name of conference

2023 IEEE 5th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA)

Labels

Sustainable Development Goals (SDG)