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A comparison of machine learning models in adverse drug side effect prediction [1]

Usage:

  • Create and activate a python environment using anaconda:

    conda env create -f py37env.yml

    conda activate py37env

    pip install qpsolvers==1.0.5

  • To generate K-Fold data

    python main.py -i

  • To run and evaluate a model:

    python main.py -d DATA_NAME -m MODEL_NAME -f FEATURE_TYPE

    For example: python main.py -d AEOLUS -m MF -f 2

    Evaluation results containing AUC, AUPR and STDERR are stored in "./results" folder.

  • To obtain options for DATA_NAME and MODEL_NAME and FEATURE_TYPE:

    python main.py -h

Data

All input data is available in the "./data" folder:

Reference

[1] Nguyen, Duc Anh, Canh Hao Nguyen, and Hiroshi Mamitsuka. "A survey on adverse drug reaction studies: data, tasks and machine learning methods." Briefings in Bioinformatics (2019).

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