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)