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

Authors

Brian Mac Namee, Technological University DublinFollow
John D. Kelleher, Technological University DublinFollow
Sarah Jane Delany, Technological University DublinFollow

Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Computer Sciences, Bioinformatics

Publication Details

In Proceedings of the Second i2b2 Shared-Task Workshop on Challenges in Natural Language Processing for Clinical Data, American Medical Informatics Association Annual conference (AMIA '08)

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.

DOI

https://doi.org/10.21427/2yxj-t186

Recommended Citation

Mac Namee, B., Kelleher, J. & Delany, S. (2008). Language Processing for Patient Diagnosis Using Text Classification and Negation Labelling. Second i2b2 Shared-Task Workshop on Challenges in Natural Language Processing for Clinical Data, American Medical Informatics Association Annual Conference (AMIA '08). doi:10.21427/2yxj-t186