Diffusion model in ICU false alarm judgement

Code/Script for IJCAI 2023 paper A Diffusion Model with Contrastive Learning for ICU False Arrhythmia Alarm Reduction.

Requirements

Dependencies can be installed by:

    pip install -r requirements.txt

Due to the requirements of the data providers, we are unable to publicly share our dataset.

To train our model, you need modify the dataset path in config/config.json file. Then you can run the train_c.py.

python train_c.py

After training is complete, run inference.py to obtain the generated curves.

python inference.py

Then run the result.ipynb to get the results.

We would like to thank Diffwave and SSSD. our code is based on their implementations.

Coming soon

Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
config		config
imputers		imputers
utils		utils
InfoNCE.py		InfoNCE.py
README.md		README.md
inference.py		inference.py
requirements.txt		requirements.txt
result.ipynb		result.ipynb
train_c.py		train_c.py