Rapid Response System Public code
Predict patient's in-hospital abnormal status for rapid response system
- Input: Patient's clinical variables (includes vital signs and laboratory tests) in an observation peroid
- Output: Patient's abnormal status/ abnormal probability
- Window time D contains the measurement features of patient in n timepoints (in the figure, n = 8)
- The window time D will slides for every timepoint for each patient
- With n = 8, for each patient, we should wait 8 hours for the first output
- After that, the system will predict once every hour
- Proposed model: Temporal Variational Autoencoder (TVAE)
- Install enviroment dependencies via 'requirement.txt'
pip install -r requirement.txt
- Install torch:
conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
- Configure the file path on the functions
- Run 'CNUH_prediction.py' for predict the outcome