Papers with detecting mental disorders
Multi-Task, Multi-Channel, Multi-Input Learning for Mental Illness Detection using Social Media Text (D19-62)
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| Challenge: | Existing methods for mental illness detection have limited data available for training . lack of sufficient annotated data and inability to extract explanations on the derived outcome have restricted researchers to use traditional methods. |
| Approach: | They propose to use emotional patterns identified by clinical practitioners to enhance the prediction capabilities of a mental illness detection model built using a deep neural network architecture. |
| Outcome: | The proposed method achieves a task-specific AUC higher than 0.90 . it compares multi-task learning with multi-channel convolutional neural network and multiple inputs to methods such as multi-class classification . |
Multi-Aspect Transfer Learning for Detecting Low Resource Mental Disorders on Social Media (2022.lrec-1)
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| Challenge: | Mental disorders are an important and pervasive public health issue. |
| Approach: | They propose to use linguistic features to improve mental disorder detection . they propose to apply multi-aspect transfer learning to detecting disorders from social media . |
| Outcome: | The proposed methods can be used to improve mental disorder detection in the context of data scarcity and understanding the overlapping symptoms between disorders. |