Medical Language Processing for Patient Diagnosis Using Text Classification and Negation Labelling

Brian Mac Namee, John Kelleher, Sarah Jane Delany

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper describes the approach of the DIT AIGroup to the i2b2 Obesity Challenge to build a system to diagnose obesity and related co-morbidities from narrative, unstructured patient records. Based on experimental results a system was developed which used knowledge-light text classification using decision trees, and negation labelling.

Conference

ConferenceSecond i2b2 Shared-Task Workshop on Challenges in Natural Language Processing for Clinical Data, American Medical Informatics Association Annual Conference
Period1/01/08 → …
OtherAMIA '08

Keywords

  • i2b2 Obesity Challenge
  • diagnose obesity
  • co-morbidities
  • narrative
  • unstructured patient records
  • knowledge-light text classification
  • decision trees
  • negation labelling

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