CURE: Context- and Uncertainty-Aware Mental Disorder Detection (2024.emnlp-main)
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| Challenge: | Existing methods to detect mental disorders focus on the presence of symptoms, but the context of symptoms is often ignored, leading to errors in symptom identification. |
| Approach: | They propose to use large language models to extract contextual information while introducing an uncertainty-aware decision fusion network that combines predictions of multiple models based on quantified uncertainty values. |
| Outcome: | The proposed model detects mental disorders even in situations where symptom information is incomplete. |
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