rbmce 0.0.2

a rule-based clinical concept extraction tool to capture microorganisms and estimate infection status on semi-structured microbiology culture reports.

RBMCE (Rule-Based Microbiology Concept Extractor):

This code was developed to provide an open-source python package to extract clinical concepts from free-text semi-structured microbiology reports. The two primary outputs for this package are (1) an binary estimation of patient bacterial infection status and (2) a list of all clinically relevant microorganisms found in the report. These outputs were validated on two independent datasets and achieved f-1 scores over 0.95 on both outputs when compared to expert review. Full details on background, algorithm, and validation results can be seen at our paper here: (currently being written, will update once submitted to archive).

🏠 Homepage

✨ package

Requirements

* python >=3.6.8
* pandas >=0.25.0

Install

pip install rbmce

Usage

Recommended datastructure:

the rbcme.run() function expects a pandas dataframe with the following elements (associated column names can be specified as kwargs):

• parsed_note:
  • microbiology report txt in either a raw or (**perferable) chopped up into components (eg gram stain/growth report/ab susceptability)
• culture_id:
  • a primary key tied to a given sample/specimen + microbiological exam order.
  • Often a microbiology order can be tied to numerous components (eg gram stain/growth report/ ab susceptability). additionally these can be appended to same report or added as a new report tied to same sample + order. all of these tied to a sample+order should share same culture_id
• visit_id:
  • primary key for patient's visit/encounter
  • can be 1-many:1 to culture_id or 1:1 (in which case can specify as culture_id)
  • in some datasets a patient may have multiple cultures performed in a visit/encounter.

Inline:

import rbmce
import pandas as pd
d={'parsed_note': 'No Salmonella, Shigella, Campylobacter, Aeromonas or Plesiomonas isolated.', 'culture_id': 1, 'visit_id': 1}
df=pd.DataFrame(data=d, index=[1])
rbmce.run(df)

Command Line:

see rbcme_run_example.py for example of an executable python file to import, format, process w/ rbmce, and save outputs (annotated dataframe, markdown_summary file)

Run tests

Inline

from rbmce import debug
test_str='No Salmonella, Shigella, Campylobacter, Aeromonas or Plesiomonas isolated.'
debug.rbmce_str_in(test_str)

Command Line:

python -m rbmce.debug 'No Salmonella, Shigella, Campylobacter, Aeromonas or Plesiomonas isolated.'

Author

👤 Garrett Eickelberg

🤝 Contributing

Contributions, issues and feature requests are welcome!
Feel free to check issues page. You can also take a look at the contributing guide

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Credits

Markdown Readme Generator

📝 License

This project is MIT licensed.

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