miade

A set of tools for extracting formattable data from clinical notes stored in electronic health record systems.

https://github.com/uclh-criu/miade

Science Score: 52.0%

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    Organization uclh-criu has institutional domain (www.uclhospitals.brc.nihr.ac.uk)
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    Low similarity (13.0%) to scientific vocabulary

Keywords

electronic-health-records natural-language-processing nlp
Last synced: 6 months ago · JSON representation ·

Repository

A set of tools for extracting formattable data from clinical notes stored in electronic health record systems.

Basic Info
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  • Open Issues: 8
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Topics
electronic-health-records natural-language-processing nlp
Created over 4 years ago · Last pushed 11 months ago
Metadata Files
Readme Contributing Code of conduct Citation

README.md

Build Status License: Elastic License 2.0

A set of tools for extracting formattable data from clinical notes stored in electronic health record systems. Powered by MedCAT models.

Installing

Install MiADE

To install the stable release: bash pip install miade

To install the latest development version of MiADE, clone this repository and run: bash pip install .

Downloading models

You may also need to download these additional models to run MiADE:

spaCy - required for MedCAT bash python -m spacy download en_core_web_md med7 - required for medication dosage extraction bash pip install https://huggingface.co/kormilitzin/en_core_med7_lg/resolve/main/en_core_med7_lg-any-py3-none-any.whl

Quickstart

Initialise MiADE with the path that you have saved your trained MedCAT models:

python miade = NoteProcessor(Path("path/to/model/dir")) Add annotators:

python miade.add_annotator("problems") miade.add_annotator("meds/allergies")

Create a note:

python text = "Patient has penicillin allergy with rash" note = Note(text)

Extract concepts:

```python concepts = miade.process(note)

for concept in concepts: print(concept)

{name: breaking out - eruption, id: 271807003, category: Category.REACTION, start: 204, end: 208, dosage: None, negex: False, meta: None}

{name: penicillin, id: 764146007, category: Category.ALLERGY, start: 191, end: 201, dosage: None, negex: False, meta: None}

```

Contributing

See contributing

Maintainers

| Name | Email | |-----------------|-----------------------------| | James Brandreth | j.brandreth@ucl.ac.uk | | Jennifer Jiang | jennifer.jiang.13@ucl.ac.uk |

Acknowledgement

This project wouldn't be possible without the work at Cogstack, spaCy, and med7!

Licence

This project is licensed under the Elastic License 2.0. See LICENSE for the full license text.

Owner

  • Name: UCLH/UCL BRC Clinical and Research Informatics Unit
  • Login: uclh-criu
  • Kind: organization

We are clinicians, AI researchers, developers and analysts working together to develop a robust environment and infrastructure for the analysis of clinical data

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below"
authors:
  - family-names: Brandreth
    given-names: James
    orchid: https://orchid.org/0000-0003-0584-0159
  - family-names: Jiang
    given-names: Jennifer
title: "MiADE"
version: 0.0.1

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  • Total packages: 1
  • Total downloads:
    • pypi 19 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 2
  • Total maintainers: 1
pypi.org: miade

A set of tools for extracting formattable data from clinical notes stored in electronic health record systems.

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 19 Last month
Rankings
Dependent packages count: 10.5%
Average: 35.0%
Dependent repos count: 59.4%
Maintainers (1)
Last synced: 7 months ago