Login / Signup

Depression Risk Prediction for Chinese Microblogs via Deep-Learning Methods: Content Analysis.

Xiaofeng WangShuai ChenTao LiWanting LiYejie ZhouJie ZhengQingcai ChenJun YanBuzhou Tang
Published in: JMIR medical informatics (2020)
We applied deep-learning methods with pretrained language representation models to automatically predict depression risk using data from Chinese microblogs. The experimental results showed that the deep-learning methods performed better than previous methods, and have greater potential to discover patients with depression and to trace their mental health conditions.
Keyphrases
  • deep learning
  • mental health
  • depressive symptoms
  • artificial intelligence
  • sleep quality
  • convolutional neural network
  • machine learning
  • autism spectrum disorder
  • electronic health record
  • climate change