From Text to Knowledge: a Unifying Document-Centered View of Analyzed Medical Language

P. Zweigenbaum; J. Bouaud; B. Bachimont; J. Charlet; B. Séroussi; J.-F. Boisvieux

doi:10.1055/s-0038-1634559

Methods of Information in Medicine, Table of Contents

Methods Inf Med 1998; 37(04/05): 384-393
DOI: 10.1055/s-0038-1634559

Original Article

Schattauer GmbH

From Text to Knowledge: a Unifying Document-Centered View of Analyzed Medical Language

Authors

P. Zweigenbaum

¹Service d'informatique médicale, Assistance Publique, Hôpitaux de Paris & Département de biomathèmatiques, Université Paris 6
J. Bouaud

¹Service d'informatique médicale, Assistance Publique, Hôpitaux de Paris & Département de biomathèmatiques, Université Paris 6
B. Bachimont

¹Service d'informatique médicale, Assistance Publique, Hôpitaux de Paris & Département de biomathèmatiques, Université Paris 6
J. Charlet

¹Service d'informatique médicale, Assistance Publique, Hôpitaux de Paris & Département de biomathèmatiques, Université Paris 6
B. Séroussi

¹Service d'informatique médicale, Assistance Publique, Hôpitaux de Paris & Département de biomathèmatiques, Université Paris 6
J.-F. Boisvieux

¹Service d'informatique médicale, Assistance Publique, Hôpitaux de Paris & Département de biomathèmatiques, Université Paris 6

Abstract

Although medical language processing (MLP) has achieved some success, the actual use and dissemination of data extracted from free text by MLP systems is still very limited. We claim that the adoption of an ‘enricheddocument’ paradigm (or ‘document-centered’ view) can help to address this issue. We present this paradigm and explain how it can be implemented, then discuss its expected benefits both for end-users and MLP researchers.

Keywords

Natural Language Processing - Medical Language - Documents

Full Text

References

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