# Mental Health Crisis Triage — References

## Data sources
- [Sentiment Analysis for Mental Health](https://www.kaggle.com/datasets/suchintikasarkar/sentiment-analysis-for-mental-health) (Suchintika Sarkar, Kaggle): 50k+ unstructured text entries labeled across Normal, Depression, Suicidal, Anxiety, Stress, Bipolar, and Personality Disorder classes.

## Models & methods
- Bi-LSTM sequence classifier for 7-class sentiment/mental health detection, with training-loop tuning for stability.
- Class-weighted cross-entropy to handle label imbalance; multi-class evaluation with F1, confusion matrices, and calibration checks.

## Technical resources & platforms
- Google Colab (Jupyter) environment running Python 3.10.
- PyTorch for deep learning; Pandas for data manipulation; Scikit-Learn for metrics; Matplotlib/Seaborn for visualization.

## AI assistance
- Google Gemini used for code generation, LSTM debugging, and refining the PyTorch training loop.