Skip to main content

Modular, fast NLP framework, compatible with Pytorch and spaCy, offering tailored support for French clinical notes.

Project description

Tests Documentation PyPI Demo Codecov DOI

EDS-NLP

EDS-NLP is a collaborative NLP framework that aims primarily at extracting information from French clinical notes. At its core, it is a collection of components or pipes, either rule-based functions or deep learning modules. These components are organized into a novel efficient and modular pipeline system, built for hybrid and multitask models. We use spaCy to represent documents and their annotations, and Pytorch as a deep-learning backend for trainable components.

EDS-NLP is versatile and can be used on any textual document. The rule-based components are fully compatible with spaCy's components, and vice versa. This library is a product of collaborative effort, and we encourage further contributions to enhance its capabilities.

Check out our interactive demo !

Features

Quick start

Installation

You can install EDS-NLP via pip. We recommend pinning the library version in your projects, or use a strict package manager like Poetry.

pip install edsnlp==0.10.7

or if you want to use the trainable components (using pytorch)

pip install "edsnlp[ml]==0.10.7"

A first pipeline

Once you've installed the library, let's begin with a very simple example that extracts mentions of COVID19 in a text, and detects whether they are negated.

import edsnlp

nlp = edsnlp.blank("eds")

terms = dict(
    covid=["covid", "coronavirus"],
)

# Split the documents into sentences, this isneeded for negation detection
nlp.add_pipe("eds.sentences")
# Matcher component
nlp.add_pipe("eds.matcher", config=dict(terms=terms))
# Negation detection
nlp.add_pipe("eds.negation")

# Process your text in one call !
doc = nlp("Le patient n'est pas atteint de covid")

doc.ents
# Out: (covid,)

doc.ents[0]._.negation
# Out: True

Documentation & Tutorials

Go to the documentation for more information.

Disclaimer

The performances of an extraction pipeline may depend on the population and documents that are considered.

Contributing to EDS-NLP

We welcome contributions ! Fork the project and propose a pull request. Take a look at the dedicated page for detail.

Citation

If you use EDS-NLP, please cite us as below.

@misc{edsnlp,
  author = {Wajsburt, Perceval and Petit-Jean, Thomas and Dura, Basile and Cohen, Ariel and Jean, Charline and Bey, Romain},
  doi    = {10.5281/zenodo.6424993},
  title  = {EDS-NLP: efficient information extraction from French clinical notes},
  url    = {https://aphp.github.io/edsnlp}
}

Acknowledgement

We would like to thank Assistance Publique – Hôpitaux de Paris, AP-HP Foundation and Inria for funding this project.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

edsnlp-0.10.7.tar.gz (1.6 MB view details)

Uploaded Source

Built Distributions

edsnlp-0.10.7-cp312-cp312-win_amd64.whl (1.9 MB view details)

Uploaded CPython 3.12 Windows x86-64

edsnlp-0.10.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

edsnlp-0.10.7-cp312-cp312-macosx_11_0_arm64.whl (1.9 MB view details)

Uploaded CPython 3.12 macOS 11.0+ ARM64

edsnlp-0.10.7-cp312-cp312-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.12 macOS 10.9+ x86-64

edsnlp-0.10.7-cp311-cp311-win_amd64.whl (1.9 MB view details)

Uploaded CPython 3.11 Windows x86-64

edsnlp-0.10.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

edsnlp-0.10.7-cp311-cp311-macosx_11_0_arm64.whl (1.9 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

edsnlp-0.10.7-cp311-cp311-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

edsnlp-0.10.7-cp310-cp310-win_amd64.whl (1.9 MB view details)

Uploaded CPython 3.10 Windows x86-64

edsnlp-0.10.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

edsnlp-0.10.7-cp310-cp310-macosx_11_0_arm64.whl (1.9 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

edsnlp-0.10.7-cp310-cp310-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

edsnlp-0.10.7-cp39-cp39-win_amd64.whl (1.9 MB view details)

Uploaded CPython 3.9 Windows x86-64

edsnlp-0.10.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

edsnlp-0.10.7-cp39-cp39-macosx_11_0_arm64.whl (1.9 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

edsnlp-0.10.7-cp39-cp39-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

edsnlp-0.10.7-cp38-cp38-win_amd64.whl (1.9 MB view details)

Uploaded CPython 3.8 Windows x86-64

edsnlp-0.10.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

edsnlp-0.10.7-cp38-cp38-macosx_11_0_arm64.whl (1.9 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

edsnlp-0.10.7-cp38-cp38-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

edsnlp-0.10.7-cp37-cp37m-win_amd64.whl (1.9 MB view details)

Uploaded CPython 3.7m Windows x86-64

edsnlp-0.10.7-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

edsnlp-0.10.7-cp37-cp37m-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

File details

Details for the file edsnlp-0.10.7.tar.gz.

File metadata

  • Download URL: edsnlp-0.10.7.tar.gz
  • Upload date:
  • Size: 1.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.18

File hashes

Hashes for edsnlp-0.10.7.tar.gz
Algorithm Hash digest
SHA256 6745732ae890f0b461d1cf072871dd4f363ffbeb29ddf10fe2ad6d97013e1045
MD5 9f0f8f00b9ead4c0b141f7f735874e4d
BLAKE2b-256 911c7a6e0b4eb8c3881b4fa70f7d81b49222da3d27a4ffff51576c27d2069008

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: edsnlp-0.10.7-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.18

File hashes

Hashes for edsnlp-0.10.7-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 eca17d34137db7387e75977b22b6ddead65d31e7526a8e919482051c8e2cc94c
MD5 ef8e055330137e8a629eadb184561512
BLAKE2b-256 7a9ae69386f4a75fb82fbaad36cdb3091887d5a24818d970ac582245a152da92

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4d568281cb74ce6e553293119cd4521e29ebc4ea0578c5f10336d2a4c428aba9
MD5 27258002426a156f1330787ccb1b4367
BLAKE2b-256 a25d76db96aa4f8ccbeb7009c32d3a4f9c3f3f1ed2099e3f51764356cf736513

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 923a1f7624193509d1bede53f6347c1c3a799c6262d820db00132a21d294c9a9
MD5 78561cede4e4742a5987dd09b8180834
BLAKE2b-256 6cec86bffa997201edaf3d855f98b6fd65e7a606743fae1936a3c183821b26bf

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp312-cp312-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp312-cp312-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0139d7a330cdba04d22b5be72d4e560b37329c11119fb75ac6cda0450296778f
MD5 238d8115e107764be41a9e553488cb3f
BLAKE2b-256 cbc55c86e716913704ed1a80807e215af8a1fc49bdadce34858191cdab492afb

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: edsnlp-0.10.7-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.18

File hashes

Hashes for edsnlp-0.10.7-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 a283cd0a3b15d3daa8df4235f4c429276224bd3a9ae3496fa25219becb07a9e3
MD5 f55c9805b136d1b6bbfb254d2f7c0a34
BLAKE2b-256 c890d30292378abcb2c4f16b1a4f6904972430f5fb858d1a38cc976c8569b2bf

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4c86f1109c12f5a505ee1d18f51942cc4035dadfb7a3ce48390668da503e696e
MD5 bb518df02af6a5bedfa147e5b2c7ea44
BLAKE2b-256 064d7b6e890265d5f72727ae344ccfd9e72a0a3b95c406f98bc52947980cf29f

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 26f8d67d2cde7ae3bb26bd8f9b157b330c04ce53f75a7fd96d4d2ad3809b1a2d
MD5 6e5f34055554b0ee2cb31fd1bd77785a
BLAKE2b-256 d2e791090cd3e8b7d9c0c827659bc320ca6d2f97f13fdfc9ce551dad491397c7

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 7449fed72222e7b33bc7b2fc88cb1f27adc46e69081288f7e22824048240fb3a
MD5 6a23fa73febfa2a66fc7fa87c782450c
BLAKE2b-256 9d97bff95ae3c0ac903d4ee3ed0ab3fa9a54d5fccd5a72c209beeb9d60953f50

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: edsnlp-0.10.7-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.18

File hashes

Hashes for edsnlp-0.10.7-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 60d3ad927b11aafc23e2e4c12fd49e12e284bccd0bee08849afe85d399e5a901
MD5 60357c3e87f061a0be0a54ea376811f3
BLAKE2b-256 ab6b9045a9907155e579a9ec72e72090a67bcd9b30c011764eb93b5e8fbe7f37

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 137625f5dcd4b3a7458ee0e5c1907db3a478fa5f3aa15b335fc36a1e5e6d6cd5
MD5 3e13529515d59c1abda85f10da872814
BLAKE2b-256 5032a40118bc199bdde41e8bce5b09898b826e46e62cbdc4f14dd91a9d95d5ed

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 fb142f0bd7171a084138fa08c6c0f389933d85f3477630e1fad5a6e3a7c01bc9
MD5 dcc8af25dcc0b0490052b5c82bda7cbd
BLAKE2b-256 2a89b1369bd3c0cbd01b7aaafe7ed2d0e235a2b60902cd97ec937d09ca8597ad

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e006c1c724a2608bc1ac4a70299e91a77337d2ce85792f2645fb27de59faaa66
MD5 f81b07f8f7d562afd0dc767036ee3324
BLAKE2b-256 04a2cfdb35ea16b133c384a9029185610d34566b6bab4da04774cc7bbdac415a

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: edsnlp-0.10.7-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.18

File hashes

Hashes for edsnlp-0.10.7-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 2083f12357b0946dbecc25a95929f940965e6126e31344df1e01203fc6f73bd8
MD5 18ac1715698c230bdd8cd7a31353bf0f
BLAKE2b-256 ca1afe4e3af95b16a21d2cc5266542c450d6a47610aa6c2cca12d44678afad21

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 134cb59fce8072af4452a28363b6a3f6f02944435b825e34b5a01dd79a3e7003
MD5 10036a5a4a0ded7a0b18219e9456fa21
BLAKE2b-256 dd5dd24dbd428f6e354e895ef893fa6e78c38354b358bdcadd0a2c4e0a1e7c3a

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 426261a8ae516d9b725107385ac6ff3f54f0aab77648b77b154436bdef928d99
MD5 7f3b0b50593c9a74b63f57c48c087672
BLAKE2b-256 5b8f5249ef53811486ed52fd3a9994a868eccbddd63952f045083e4e18706281

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 45988f8ae30d0a628961237d64a6d67fc5d77188a2b75ffb76f91fda1c2210e9
MD5 fe944a64664cdea1b0d437b52b487c02
BLAKE2b-256 3b9fe201dc4346d40b7a94c9f362fa3c1ea4a94f0327e168b08a2d5c42837cf7

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: edsnlp-0.10.7-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.18

File hashes

Hashes for edsnlp-0.10.7-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 848123ea6846f2d1de69e6a5fb79eaaac6c56f819895a1f9b61526ab65ffe0e9
MD5 596877f9c81628f77c2bb93f2b3f7fe0
BLAKE2b-256 be4adc0e0bd8747fbd450a79811dc33c054408a9aae1b572ee7862f7dc7f3e85

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b94a58e74600ef00ac88164c49ce323faa353d82ea699ed1e4f0e4cc2d9ea070
MD5 e2132598cc25b97f07bc9e78ed3de820
BLAKE2b-256 8324edb5ea7861f0934b7ba8e202b857059654325352447ab82bb91182c9fd37

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 5e7e548d10d60694de6d687302c49e58789119f21e67536ff759d2d76e1e42a5
MD5 a0abd27f47d84ab5659245ed60d1fa09
BLAKE2b-256 c4775c14590c41fa2071843eb5b15d80dc7b4ea8043ac3ab500220fb98847d73

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 25900febe0bf0ec03719caa3421a392d68ade39984a45910b0142ca3ede4fe34
MD5 14fd2caf741e4af43dd74334f932e46d
BLAKE2b-256 27a41250f85f49da22430d64f78db595d4f427dc3e0a3c703555d4b2b7b5d45f

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: edsnlp-0.10.7-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 1.9 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.18

File hashes

Hashes for edsnlp-0.10.7-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 592fc61ac7738ea3dd5e49708f3759bc0c725f36d436905f769e56abe98149b7
MD5 1885ae81e93161b5657a7d9fb743b725
BLAKE2b-256 2d25241b6f535753ecf8bc09266d8e7af28334ffcf7555a246f374c5d811a2d0

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 221d51c9158e53b657f9801b3ce79d2c050c41969a73a1c2485619e973ee432f
MD5 5c1fbd7b4dc8a14bf1a748202b018098
BLAKE2b-256 7062f1063ac1c2ad78ec56780c0c1743bf2ff950c00dd0ee7ff11e97053bc43b

See more details on using hashes here.

Provenance

File details

Details for the file edsnlp-0.10.7-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for edsnlp-0.10.7-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e71a2bde042bdf46ef7a7c842b2332cb062b6cc318550a3426df767c6f6fa220
MD5 fbd6006f88c217bec4d21a9d0812675a
BLAKE2b-256 5fbb737cf040986edf48f2e092a9abddf61996ba30014f3e130f1337344eb952

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page