EmoTrack: Robust Depression Tracking from Counseling Transcripts across Session Regimes
Learn how EmoTrack tracks depression from counseling transcripts, improving AI mental health support and timely human intervention, by leveraging robust PHQ-8 prediction across session regimes
- Build a dataset of counseling transcripts with corresponding PHQ-8 scores
- Fine-tune a pre-trained language model on the dataset to improve PHQ-8 prediction
- Configure EmoTrack to handle varying session regimes and data scarcity
- Test EmoTrack's performance on a held-out test set
- Apply EmoTrack to real-world counseling transcripts for depression tracking
Mental health professionals and AI engineers can benefit from EmoTrack, as it enables more accurate monitoring of depression severity and flags sessions requiring human review, allowing for timely intervention and improved patient care
💡 Robust PHQ-8 prediction across session regimes is crucial for effective AI mental health support, and EmoTrack achieves this through a combination of fine-tuning and data-efficient methods
🤖 EmoTrack: AI-powered depression tracking from counseling transcripts 📝
Key Takeaways
Learn how EmoTrack tracks depression from counseling transcripts, improving AI mental health support and timely human intervention, by leveraging robust PHQ-8 prediction across session regimes
DeepCamp AI