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/ code source to create the set of MeSH qualifiers from PubMed
  • source/ 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/ 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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