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MIT License | ||
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Copyright (c) 2020 Ferran Gonzalez Hernandez | ||
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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: | ||
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The above copyright notice and this permission notice shall be included in all | ||
copies or substantial portions of the Software. | ||
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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. |
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# PKDocClassifier | ||
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This repository provides the code for developing a machine learning pipeline that classifies scientific publications from PubMed depending on whether they report new pharmacokinetic (PK) parameters from __in vivo__ studies. | ||
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In the analyses section the different pipelines.. | ||
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The final pipeline retrieved more than 120K PK publications and runs weekly updates. All the retrieved data has been arranged at https://stage-app.pkpdai.com/. | ||
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# Reproducing our results | ||
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## 1. Installation | ||
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## 2. Data download | ||
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## 3. Run |
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# This file may be used to create an environment using: | ||
# $ conda env create --name <env> --file <this file> | ||
# platform: linux-64 | ||
name: fgh95 | ||
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channels: | ||
- conda-forge | ||
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dependencies: | ||
- python=3.7 | ||
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- pip: | ||
- -r file:requirements.txt |
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from setuptools import setup, find_packages | ||
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with open('requirements.txt') as f: | ||
requirements = f.read().splitlines() | ||
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setup( | ||
name="pk_classifier", | ||
version="0.1.0", | ||
packages=find_packages(), | ||
install_requires=requirements | ||
) |