| Name | PyRuSH JSON |
| Version |
1.0.9
JSON |
| download |
| home_page | https://github.com/jianlins/PyRuSH |
| Summary | PyRuSH is the python implementation of RuSH (Rule-based sentence Segmenter using Hashing), which is originally developed using Java. RuSH is an efficient, reliable, and easy adaptable rule-based sentence segmentation solution. It is specifically designed to handle the telegraphic written text in clinical note. It leverages a nested hash table to execute simultaneous rule processing, which reduces the impact of the rule-base growth on execution time and eliminates the effect of rule order on accuracy. |
| upload_time | 2024-10-27 14:46:29 |
| maintainer | None |
| docs_url | None |
| author | Jianlin |
| requires_python | >=3.6 |
| license | MIT License Copyright (c) 2020 Jianlin Shi Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
pyrush
nlp
sentenczier
sentence segmentation
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
PyRuSH
=========
PyRuSH is the python implementation of `RuSH <https://github.com/jianlins/RuSH>`_ (**Ru** le-based sentence **S** egmenter using **H** ashing), which is originally developed using Java. RuSH is an efficient, reliable, and easy adaptable rule-based sentence segmentation solution. It is specifically designed to handle the telegraphic written text in clinical note. It leverages a nested hash table to execute simultaneous rule processing, which reduces the impact of the rule-base growth on execution time and eliminates the effect of rule order on accuracy.
If you wish to cite RuSH in a publication, please use:
Jianlin Shi ; Danielle Mowery ; Kristina M. Doing-Harris ; John F. Hurdle.RuSH: a Rule-based Segmentation Tool Using Hashing for Extremely Accurate Sentence Segmentation of Clinical Text. AMIA Annu Symp Proc. 2016: 1587.
The full text can be found `here <https://knowledge.amia.org/amia-63300-1.3360278/t005-1.3362920/f005-1.3362921/2495498-1.3363244/2495498-1.3363247?timeStamp=1479743941616>`_.
Installation
------------
pip install PyRuSH
How to use
------------
A standalone RuSH class is available to be directly used in your code. From 1.0.4, pyRush adopt spaCy 3.x api to initiate an component.
>>> from PyRuSH import RuSH
>>> input_str = "The patient was admitted on 03/26/08\n and was started on IV antibiotics elevation" +\
>>> ", was also counseled to minimizing the cigarette smoking. The patient had edema\n\n" +\
>>> "\n of his bilateral lower extremities. The hospital consult was also obtained to " +\
>>> "address edema issue question was related to his liver hepatitis C. Hospital consult" +\
>>> " was obtained. This included an ultrasound of his abdomen, which showed just mild " +\
>>> "cirrhosis. "
>>> rush = RuSH('../conf/rush_rules.tsv')
>>> sentences=rush.segToSentenceSpans(input_str)
>>> for sentence in sentences:
>>> print("Sentence({0}-{1}):\t>{2}<".format(sentence.begin, sentence.end, input_str[sentence.begin:sentence.end]))
Spacy Componentized PyRuSH
---------------------------
Start from version 1.0.3, PyRuSH adds Spacy compatible Sentencizer component: PyRuSHSentencizer.
>>> from PyRuSH import PyRuSHSentencizer
>>> from spacy.lang.en import English
>>> nlp = English()
>>> nlp.add_pipe("medspacy_pyrush")
>>> doc = nlp("This is a sentence. This is another sentence.")
>>> print('\n'.join([str(s) for s in doc.sents]))
A Colab Notebook Demo
---------------------------
Feel free to try this runnable `Colab notebook Demo <https://colab.research.google.com/drive/1gX9MzZTQiPw8G3x_vUwZbiSXGtbI0uIX?usp=sharing>`_
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"description": "PyRuSH\n=========\n\n\n\nPyRuSH is the python implementation of `RuSH <https://github.com/jianlins/RuSH>`_ (**Ru** le-based sentence **S** egmenter using **H** ashing), which is originally developed using Java. RuSH is an efficient, reliable, and easy adaptable rule-based sentence segmentation solution. It is specifically designed to handle the telegraphic written text in clinical note. It leverages a nested hash table to execute simultaneous rule processing, which reduces the impact of the rule-base growth on execution time and eliminates the effect of rule order on accuracy.\n\nIf you wish to cite RuSH in a publication, please use:\n\nJianlin Shi ; Danielle Mowery ; Kristina M. Doing-Harris ; John F. Hurdle.RuSH: a Rule-based Segmentation Tool Using Hashing for Extremely Accurate Sentence Segmentation of Clinical Text. AMIA Annu Symp Proc. 2016: 1587.\n\nThe full text can be found `here <https://knowledge.amia.org/amia-63300-1.3360278/t005-1.3362920/f005-1.3362921/2495498-1.3363244/2495498-1.3363247?timeStamp=1479743941616>`_.\n\n\n\nInstallation\n------------\n\n pip install PyRuSH\n\n\nHow to use\n------------\n\nA standalone RuSH class is available to be directly used in your code. From 1.0.4, pyRush adopt spaCy 3.x api to initiate an component.\n\n >>> from PyRuSH import RuSH\n >>> input_str = \"The patient was admitted on 03/26/08\\n and was started on IV antibiotics elevation\" +\\\n >>> \", was also counseled to minimizing the cigarette smoking. The patient had edema\\n\\n\" +\\\n >>> \"\\n of his bilateral lower extremities. The hospital consult was also obtained to \" +\\\n >>> \"address edema issue question was related to his liver hepatitis C. Hospital consult\" +\\\n >>> \" was obtained. This included an ultrasound of his abdomen, which showed just mild \" +\\\n >>> \"cirrhosis. \"\n >>> rush = RuSH('../conf/rush_rules.tsv')\n >>> sentences=rush.segToSentenceSpans(input_str)\n >>> for sentence in sentences:\n >>> print(\"Sentence({0}-{1}):\\t>{2}<\".format(sentence.begin, sentence.end, input_str[sentence.begin:sentence.end]))\n \nSpacy Componentized PyRuSH\n---------------------------\nStart from version 1.0.3, PyRuSH adds Spacy compatible Sentencizer component: PyRuSHSentencizer.\n\n >>> from PyRuSH import PyRuSHSentencizer\n >>> from spacy.lang.en import English\n >>> nlp = English()\n >>> nlp.add_pipe(\"medspacy_pyrush\")\n >>> doc = nlp(\"This is a sentence. This is another sentence.\")\n >>> print('\\n'.join([str(s) for s in doc.sents]))\n \n\n \nA Colab Notebook Demo\n---------------------------\nFeel free to try this runnable `Colab notebook Demo <https://colab.research.google.com/drive/1gX9MzZTQiPw8G3x_vUwZbiSXGtbI0uIX?usp=sharing>`_\n",
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