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CLT Seminar: Stefan Schulz - Automated codification of medical documents

SEMINAR

Stefan Schulz (Freiburg) - Automated codification of medical documents

Abstract:

The advance of electronic health records not only in industrialized countries but also in the developing world has made large amounts of medical narratives electronically available. These texts exhibit special characteristics, such as un- and paragrammatical sentences, the use of acronyms and abbreviations, and the abundance of typing errors.

In a case study from a Brazilian university hospital, selected content of medical discharge summaries in Portuguese was automatically mapped to SNOMED CT, a comprehensive medical terminology. SNOMED CT provides (chiefly multi-word) English and Spanish terms. In order to optimally align text sequences and terms, token chains that exhibited term-typical POS tags were selected from the source. These term candidates, together with all SNOMED terms, were  submitted to a morphosemantic normalization process, which consists of the extraction of meaningful subwords and their mapping to a language-independent interlingua.

The accuracy of the mapping, measured against a gold standard built by two domain experts (kappa 0.89) ranged from 0.66 for two-word terms to 0.89 for five-word terms.

Schulz on the web

Date: 2010-10-08 10:15 - 12:00

Location: L307, Lennart Torstenssonsgatan 8

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Page updated: 2010-09-17 10:06

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