Making shallow look deeper: anaphora and comparisons in medical information extraction

• Autorzy: Mykowiecka A. , Marciniak M. , Kupść A.
• Konferencja: Human Language Technologies as a challenge for Computer Science and Linguistics (2; 21-23.04.2005; Poznań, Poland)
• Języki publikacji: EN

Abstrakty

EN

The paper focuses on resolving natural language issues which have been affecting performance of our system processing Polish medical data. In particular, we address phenomena such as ellipsis, anaphora, comparisons, coordination and negation occurring in mammogram reports. We propose practical data-driven solutions which allow us to improve the systems performance.

Słowa kluczowe

EN

information extraction; shallow parsing; anaphoric expressions

• Wydawca: Polish Academy of Sciences, Committee of Automatic Control and Robotics
• Czasopismo: Archives of Control Sciences
• Rocznik: 2005
• Tom: Vol. 15, no. 3
• Strony: 371--380
• Opis fizyczny: Bibliogr. 10 poz., rys.

Twórcy

autor

Mykowiecka A.

• Institute of Computer Science, Polish Academy of Sciences, Ordona 21, 01-237 Warsaw, Poland

autor

Marciniak M.

• Institute of Computer Science, Polish Academy of Sciences, Ordona 21, 01-237 Warsaw, Poland

autor

Kupść A.

• CNRS, LORIA UMR 7503, BP 239 Campus Scientifique, 54506 Vandoeuyre-les-Nancy, FranceS

Bibliografia

• [1] M. Becker, W. Drożdżyński, H. Krieger, J. Piskorski, U. Schaefer and F. Xu: SProUT — Shallow Processing with Typed Feature Structures and Unification. In Prot. ICON 2002, Mumbai. India. (2002).
• [2] U. Hahn, M. Romacker and S. Schultz: Medsyndikate — a natural language system for the extraction of medical information from findings reports, hit. J. Medical Informatics. (2002). 63-74.
• [3] G. Hripcsak, J. Austin, P. Anderson and C. Friedman: Use of natural language processing to translate clinical information from a database of 889.921 chest radiographic reports. Radiology, 224 (2002).
• [4] G. Hripcsak, C. Friedman and P. Alderson: Unlocking clinical data from narrative reports. Annals of Internal Medicine, 122 ( 1995).
• [5] N. L. Jain and C. Friedman: Identification of Findings Suspicious for Breast Cancer Based on Natural Language processing of mammogram reports. In Pmc. American Medical Informatics Association Annual Fall Symp.. ( 1997). 829-833.
• [6] A. Kupść, M. Marciniak, A. Mykowiecka, J. PiskorskiI and T. Podsiadly-Marczynkowska: Information extraction from mammogram reports. In Prot: KONVENS 2004, Schriftenreihe der Österreichischen Gesellschaft fur Artificial Intelligence, (2004). 113-116.
• [7] M. Marciniak, A. Mykowiecka, A. Kupść and J. Piskorski: Intelligent content extraction from polish medical reports. Proc. Of lCMIT. PJWSTK. (2004).
• [8| A. Mykowiecka, A. Kupść and M. Marciniak: Rule-based medical content extraction and classification. In Proc. ISMIS. Gdansk. Springer-Verlag. (2005).
• [9| J. Piskorski, P. Homola, M. Marciniak, A. Mykowiecka, A. Przepiórkowski, and M. Woliński: Information Extraction for Polish Using the SProUT Platform. Intelligent Information Processing and Web Mining. Proc. of the IIS '04 Conf, Zakopane. Springer. (2004).
• [10] K. R. Taira, G. S. G. Soderland and R. M. Jakobovits: Automatic structuring of radiology free-text reports. Radiographics. 21 (2001).