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Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology Automated coding of diagnoses - three methods compared Presenter.

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Presentation on theme: "Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology Automated coding of diagnoses - three methods compared Presenter."— Presentation transcript:

1 Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology Automated coding of diagnoses - three methods compared Presenter : Shao-Wei Cheng Authors : Pius Franz, Albrecht Zaiss, Stefan Schulz, Udo Hahn, Rüdiger Klar AMIA 2000

2 Intelligent Database Systems Lab N.Y.U.S.T. I. M. 2 Outline Motivation Objective Methodology Experiments Conclusion Personal Comments

3 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Motivation In Germany, new legal requirements have raised the importance of the accurate encoding of admission and discharge diseases for in- and outpatients. 3 ?

4 Intelligent Database Systems Lab N.Y.U.S.T. I. M. 4 Objectives In response to emerging needs for computer-supported tools, this paper examined three methods for automated coding of German-language free-text diagnosis phrases. ? √

5 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Methodology SNOMED encoding ( MSVS and MSMS )  Preprocessing  Morphological Segmentation  SNOMED Indexing MedSearch retrieval  Ranking of Retrieval Terms  Exploitation of the SNOMED Hierarchy  Retrieval Algorithm 5 Stems, like gastr, hepat, diaphys, Prefixes, like a, de, in, ent, ver, anti, Infixes (e.g., o in gastr-o-intestinal) Derivational suffixes, such as io, ion, ung, Inflectional suffixes, like e, en, s, idis, ae, oris, Eponyms, digits and acronyms like AIDS, ECG, Stems  ad Prefixes  dec ( 十的意思 ) Inflectional suffixes  e  Decad ( 十個構成一組 )  Decade ( 十年 )

6 Intelligent Database Systems Lab N.Y.U.S.T. I. M. Experiments 6

7 Intelligent Database Systems Lab N.Y.U.S.T. I. M. 7 Conclusion A satisfactory quality of automated encoding of free-text diagnoses into ICD is not yet reached. From these results we deduce the following requirements for further work  With a comprehensive Thesaurus of Diagnoses, a better support of the clinical jargon will be given.  A mapping to synonymous expressions can already be done at the level of lexical morphemes.  The latter, provided a formal reconstruction of the ICD, would allow for substituting ICD disease encoding by SNOMED disease encoding.

8 Intelligent Database Systems Lab N.Y.U.S.T. I. M. 8 Personal Comments Advantage  … Drawback  … Application  Information retrieval.


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