https://github.com/jalajthanaki/medical_notes_extractive_summarization
Extractive summarizationof medical transcriptions
https://github.com/jalajthanaki/medical_notes_extractive_summarization
extractive-text-summarization medical-data ranking-algorithm summarization tf-idf-vectorizer
Last synced: 2 months ago
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Extractive summarizationof medical transcriptions
- Host: GitHub
- URL: https://github.com/jalajthanaki/medical_notes_extractive_summarization
- Owner: jalajthanaki
- Created: 2018-04-12T11:36:31.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2018-04-14T11:29:40.000Z (about 7 years ago)
- Last Synced: 2025-03-23T18:54:20.746Z (3 months ago)
- Topics: extractive-text-summarization, medical-data, ranking-algorithm, summarization, tf-idf-vectorizer
- Language: Python
- Homepage:
- Size: 12.7 KB
- Stars: 8
- Watchers: 1
- Forks: 9
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Extractive summarization of medical transcriptions
This repository contains the code which can generate extractive summary of medical transcription documents
## Dependencies
* numpy
* scipy
* nltk
* scikit-learn
* pattern
* pyteaser
* sumy
## Install
```
numpy: $ sudo pip install numpy
nltk: $ sudo pip install nltk
scipy: $ sudo pip install scipy
scikit-learn: $ sudo pip install sklearn
pattern: $ sudo pip install pattern
pyteasaer: $ sudo pip install pyteaser
summy: $ sudo pip install sumy
```
## Usage
* For running base-line approach run the `pyteaser_demo.py` and `sumy_demo.py` files which are put inside the Base_line_approach folder
* For running revised approach run the `summarize.py` file which is put inside the Revised_approach folder
* For running best approach run the `document_summarization.py` file which is put inside Best_approach folder
## Credit
Code credits for this code go to dipanjanS, Xiao and Tristan Havelick. I've merely created a wrapper and necessary changes to get people started.