cyclops is a toolkit for facilitating research and deployment of ML models for healthcare. It provides a few high-level APIs namely:
data- Create datasets for training, inference and evaluation. We use the popular 🤗 datasets to efficiently load and slice different modalities of datamodels- Use common model implementations using scikit-learn and PyTorchtasks- Use common ML task formulations such as binary classification or multi-label classification on tabular, time-series and image dataevaluate- Evaluate models on clinical prediction tasksmonitor- Detect dataset shift relevant for clinical use casesreport- Create model report cards for clinical ML models
cyclops also provides example end-to-end use case implementations on clinical datasets such as
🐣 Getting Started
Installing cyclops using pip
python3 -m pip install pycyclops
cyclops has many optional dependencies that are used for specific functionality. For
example, the monai library is used for loading
DICOM images to create datasets. Hence, monai can be installed using
python3 -m pip install pycyclops[monai]. Specific sets of dependencies are listed
below.
| Dependency | pip extra | Notes |
|---|---|---|
| xgboost | xgboost | Allows use of XGBoost model |
| torch | torch | Allows use of PyTorch models |
| torchvision | torchvision | Allows use of Torchvision library |
| torchxrayvision | torchxrayvision | Uses TorchXRayVision library |
| monai | monai | Uses MONAI to load and transform images |
| alibi | alibi | Uses Alibi for additional explainability functionality |
| alibi-detect | alibi-detect | Uses Alibi Detect for dataset shift detection |
🧑🏿💻 Developing
Using poetry
The development 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
In order to install dependencies for testing (codestyle, unit tests, integration tests), run:
python3 -m poetry install --with test
API documentation is built using Sphinx and can be locally built by:
python3 -m poetry install --with docs
cd docs
make html SPHINXOPTS="-D nbsphinx_allow_errors=True"
Contributing
Contributing to cyclops is welcomed. See Contributing for guidelines.
📚 Documentation
If you need to build the documentations locally, make sure to install Pandoc in addition to docs poetry group.
📓 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>.
🎓 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}
}
1 maintainer
Metadata
1 maintainer
Release files for pycyclops 0.2.12
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pycyclops-0.2.12.tar.gz | 303.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pycyclops-0.2.12-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 713.8 kB
Release files / pycyclops-0.2.12.tar.gz
| Download URL | pycyclops-0.2.12.tar.gz |
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| Tags | Python 3 |
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