https://github.com/rbroc/multidiagnosis-text

Feature-based and Transformer models for classification of mental disorders from text
https://github.com/rbroc/multidiagnosis-text

machine-learning nlp psychiatry text

Last synced: 28 days ago
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Feature-based and Transformer models for classification of mental disorders from text

• Host: GitHub
• URL: https://github.com/rbroc/multidiagnosis-text
• Owner: rbroc
• License: mit
• Created: 2023-09-18T09:02:03.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-09-18T12:42:53.000Z (over 1 year ago)
• Last Synced: 2024-10-24T11:52:07.109Z (3 months ago)
• Topics: machine-learning, nlp, psychiatry, text
• Language: Jupyter Notebook
• Homepage: https://arxiv.org/abs/2301.06916
• Size: 20.3 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
### Multi-class diagnosis prediction using text

Code for training feature-based baselines and Transformer models for classification of mental disorders from text, both in a multiclass classification setting and in a binary classification setting.

- `train_baselines.py` contains code to train a variety of feature-based XGboost baselines, and baselines based on static vectors;

- `train_transformer.py` contains code to train transformer-based classifiers;

- `train_classifier.py` contains code to run baselines as classifications with a shallow neural network.

- `preproc.py` and `dataset.py` are dataset processing utils (data not shared due to confidentiality)

The repository also includes additional utils and notebook for exploration of the results.

Models and their predictions are logged under `logs`. Aggregate model performance is reported in `logs/aggregates`, which also contains results from speech-based models.

The twin repository for audio-based models is here: https://github.com/HLasse/multidiagnosis-speech

Related publication (available [here](https://arxiv.org/abs/2301.06916)):

Hansen, L., Rocca, R., Simonsen, A., Parola, A., Bliksted, V., Ladegaard, N., ... & Fusaroli, R. (2023). Automated speech-and text-based classification of neuropsychiatric conditions in a multidiagnostic setting. arXiv preprint arXiv:2301.06916.