DeepMood: Forecasting Depressed Mood Based on Self-Reported Histories via Recurrent Neural Networks

@inproceedings{Suhara2017DeepMoodFD,
  title={DeepMood: Forecasting Depressed Mood Based on Self-Reported Histories via Recurrent Neural Networks},
  author={Yoshihiko Suhara and Yinzhan Xu and Alex 'Sandy' Pentland},
  booktitle={WWW},
  year={2017}
}
Depression is a prevailing issue and is an increasing problem in many people’s lives. Without observable diagnostic criteria, the signs of depression may go unnoticed, resulting in high demand for detecting depression in advance automatically. This paper tackles the challenging problem of forecasting severely depressed moods based on self-reported histories. Despite the large amount of research on understanding individual moods including depression, anxiety, and stress based on behavioral logs… CONTINUE READING

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