Multi-task adapters and task similarity for efficient extraction of pathologies from medical reports

An apparatus for processing text data, the apparatus comprising:

• at least one memory;
• and
• at least one processor coupled to the at least one memory, the at least one processor configured to:
• obtain an input text data, the input text data indicative of one or more pathologies associated with a corresponding radiological image, wherein the one or more pathologies are included in a plurality of pathologies;
• generate, using a Bidirectional Encoder Representations from Transformers (BERT)-based machine learning network, a plurality of location tags associated with the input text data, wherein each respective location tag of the plurality of location tags is associated with a sentence included in the input text data and is indicative of an anatomical location;
• generate a plurality of sentence groups based on the input text data and the plurality of location tags, wherein each sentence group of the plurality of sentence groups includes one or more sentences that are included in the input text data and are associated with a respective location tag indicative of a same respective anatomical location;
• and
• generate, using a multi-task learning (MTL)-based machine learning network, a plurality of sets of features, wherein each set of features of the plurality of sets of features:
• is generated based on a particular sentence group of the plurality of sentence groups;
• and
• is indicative of a plurality of pathology severity predictions determined for the respective anatomical location associated with the particular sentence group.