Early Detection of Depression Using Machine Learning and Social Well-Being Survey Data-Reference-Cited by-同舟云学术

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Early Detection of Depression Using Machine Learning and Social Well-Being Survey Data

Published:2024-03-14 Issue: Volume:30 Page:181-186
ISSN:
Container-title:2024 16th International Conference on Computer and Automation Engineering (ICCAE)
language:
Short-container-title:

Author:

Wang Alex X.¹,Nguyen Binh P.¹,Elliott Tom²,Mbinta James F.²,Sporle Andrew³,Simpson Colin R.²

Affiliation:

1. School of Mathematics and Statistics, Victoria University of Wellington,Wellington,New Zealand

2. Victoria University of Wellington,Wellington Faculty of Health,Wellington,New Zealand

3. School of Social Sciences, The University of Auckland,Auckland,New Zealand

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10569140/10569143/10569222.pdf?arnumber=10569222

Reference20 articles.

1. Optuna

2. Effects of home confinement on mental health and lifestyle behaviours during the COVID-19 outbreak: Insight from the ECLB-COVID19 multicenter study

3. Predicting Psychological Distress During the COVID-19 Pandemic: Do Socioeconomic Factors Matter?

4. The effect of psychotherapeutic interventions on positive and negative affect in depression: A systematic review and meta-analysis

5. The relation between age and experienced stress, worry, affect, and depression during the spring 2020 phase of the COVID-19 pandemic in the United States.

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