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ABSTRACT

In this paper, we extend previous work on the automatic structuring of medical documents using content analysis. Our long-term objective is to take advantage of specific rhetoric markers encountered in specialized medical documents (clinical guidelines) to automatically structure free text according to its role in the document. This should enable to generate multiple views of the same document depending on the target audience, generate document summaries, as well as facilitating knowledge extraction from text. We have established in previous work that the structure of clinical guidelines could be refined through the identification of a limited set of deontic operators. We now propose to extend this approach by analyzing the text delimited by these operators using Rhetorical Structure Theory. The emphasis on causality and time in RST proves a powerful complement to the recognition of deontic structures while retaining the same philosophy of high-level recognition of sentence structure, which can be converted into application-specific mark-ups. Throughout the paper, we illustrate our findings through results produced by the automatic processing of English guidelines for the management of hypertension and Alzheimer disease.

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INDEX TERMS

Primary Classification:
  J. Computer Applications
  J.3 LIFE AND MEDICAL SCIENCES
      Subjects: Medical information systems

Additional Classification:
  I. Computing Methodologies
  I.7 DOCUMENT AND TEXT PROCESSING
      I.7.2 Document Preparation
          Subjects: Hypertext/hypermedia; Markup languages

General Terms:
Algorithms, Documentation, Languages

Keywords:
medical document processing, natural language processing