---

cyclops is a framework for facilitating research and deployment of ML models in the health (or clinical) setting. It provides a few high-level APIs namely:

• query - Querying EHR databases (such as MIMIC-IV)
• process - Process static and temporal EHR data
• evaluate - Evaluate models on clinical prediction tasks
• monitor - Detect data drift relevant for clinical use cases

cyclops also provides a library of use-cases on clinical datasets. The implemented use cases include:

• Mortality decompensation prediction

🐣 Getting Started

Installing cyclops using pip

python3 -m pip install pycyclops

The core package only includes support for the process API. To install support for query, evaluate and monitor APIs, install them as extra dependency installs.

To install with query API support,

python3 -m pip install 'pycyclops[query]'

To install with evaluate API support,

python3 -m pip install 'pycyclops[evaluate]'

To install with monitor API support,

python3 -m pip install 'pycyclops[monitor]'

Multiple extras could also be combined, for example to install with both query and evaluate API support:

python3 -m pip install 'pycyclops[query,evaluate]'

🧑🏿‍💻 Developing

The development environment has been tested on python = 3.9.

The python virtual environment can be set up using poetry. Hence, make sure it is installed and then run:

python3 -m poetry install
source $(poetry env info --path)/bin/activate

Contributing

Contributing to cyclops is welcomed. See Contributing for guidelines.

📚 Documentation

📓 Notebooks

To use jupyter notebooks, the python virtual environment can be installed and used inside an IPython kernel. After activating the virtual environment, run:

python3 -m ipykernel install --user --name <name_of_kernel>

Now, you can navigate to the notebook's Kernel tab and set it as <name_of_kernel>.

Tutorial notebooks in docs/source/tutorials can be useful to view the functionality of the framework.

🎓 Citation

Reference to cite when you use CyclOps in a project or a research paper:

@article {Krishnan2022.12.02.22283021,
	author = {Krishnan, Amrit and Subasri, Vallijah and McKeen, Kaden and Kore, Ali and Ogidi, Franklin and Alinoori, Mahshid and Lalani, Nadim and Dhalla, Azra and Verma, Amol and Razak, Fahad and Pandya, Deval and Dolatabadi, Elham},
	title = {CyclOps: Cyclical development towards operationalizing ML models for health},
	elocation-id = {2022.12.02.22283021},
	year = {2022},
	doi = {10.1101/2022.12.02.22283021},
	publisher = {Cold Spring Harbor Laboratory Press},
	URL = {https://www.medrxiv.org/content/early/2022/12/08/2022.12.02.22283021},
	journal = {medRxiv}
}