MeSH2Matrix - A set of Python codes for the generation of biomedical ontologies from the MeSH keywords of the PubMed scholarly publications

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Data Analysis MeSH2Matrix
Overview

MeSH2Matrix

A set of Python codes for the generation of biomedical ontologies from the MeSH keywords of the PubMed scholarly publications

Description of Output Files

  • output/rellist.tsv: list of relations (size of 81k)
  • output/sample.txt: Set of MeSH qualifiers Associations extracted from PubMed
  • output/label_encoded.csv: Encoding for the 195 unique labels

Description of Sources Files

  • source/extract_mesh.py: code source to create the set of MeSH qualifiers from PubMed
  • source/generate_matrices.py: Generate the dataset for the modeling part. Each line is the tuple (relation_matrix, label) where relation_matrix is a (89, 89) matrix.
    • Current Statistics:
      • Dataset Size and shape: 46469, (46469, 89, 89)
      • Unique Labels: 195
      • Labels Set Shape: (46469,)
  • source/main.py: Download our existing data set and return a tuple of arrays: (train_data, train_labels), (dev_data, dev_labels) and (test_data, test_labels)

    Add: --save or -s to save the train, dev and test numpy files | --downloaded or -d if the files have already been downloaded.

    • Train Set: (33457, 89, 89)
    • Dev Set: (13012, 89, 89)
    • Test Set: (9294, 89, 89)
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Comments
  • compare mesh2matrix approach to existing works (extension work)

    compare mesh2matrix approach to existing works (extension work)

    We need to compare the mesh2matrix approach to existing methods (relying mainly on text).

    Some papers I found which could help:

    Workflow:

    • Find out the simplest method used on text (probably SVM) and understand what kind of text they use (abstract, whole article, specific sentences from article?)
    • Run the new version of extract_mesh.py which will extract the required text from 1. above
    • Compare that the new dataset is the same as we used for initial modelling (if it isn't might need to run both from scratch).
    • Run models and compare.
    • As an extension, could try to work mesh2matrix on existing benchmark corpora (like ChemProt, BioInfer, etc).
    opened by chrisemezue 0
Owner
SisonkeBiotik
SisonkeBiotik
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