A hierarchical approach to encoding medical concepts for clinical notes

Authors:
Yitao Zhang
Affiliations:
The University of Sydney, NSW, Australia
Venue:
HLT-SRWS '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Student Research Workshop
Year:
2008

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Abstract

This paper proposes a hierarchical text categorization (TC) approach to encoding free-text clinical notes with ICD-9-CM codes. Preliminary experimental result on the 2007 Computational Medicine Challenge data shows a hierarchical TC system has achieved a micro-averaged F1 value of 86.6, which is comparable to the performance of state-of-the-art flat classification systems.