Lifeback-Depression Detection

Problem Statement

Depression is a common mental disorder, which can happen to anyone at any stage of Ilife. In most cases, it is not recognizable even by the person who is suffering from it. The main goal of this project is to detect whether a person is depressed or not and then identify the level of depression the person is suffering from.

The objectives of the project are –
i) To aid doctors (currently of RML hospital) with an automated tool to assist depression detection.

ii) To develop a state of the art model for multimodal depression detection in different scenarios.

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Technologies Used

For the AI part:
  • CNNs, RNNs, LSTMs and similar deep learning algorithms
  • Transformers
  • Graph Convolutional Networks(RGCN, GraphConv)
 
Frameworks for Tools:
  • Canva for design
  • Flask
  • MongoDB
  • Angular
  • JWT for encryption