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Generalizability of machine learning in predicting antimicrobial resistance in E. coli: a multi-country case study in Africa

This repository contains the required python scripts and associated data to train and test Machine Learning (ML) models using most classifiers supported by the python ski-learn and associated packages in a Linux environment. The majority of ML scripts have been provided as jupyter notebook files (.ipynb) to enhance users ability to break the scripts down into manageable and understandable sections.

Associated Publication

The methodology underlying the framework has been detailed in the manuscript "Generalizability of machine learning in predicting antimicrobial resistance in E. coli: a multi-country case study in Africa" published in BMC Genomics. Please refer to citation information at the bottom of this document(TBD)

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  • Jupyter Notebook 99.5%
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