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<Paper uid="A97-1027">
  <Title>Dutch Sublanguage Semantic Tagging combined with Mark-Up Technology</Title>
  <Section position="7" start_page="185" end_page="189" type="concl">
    <SectionTitle>
4 Future Research
</SectionTitle>
    <Paragraph position="0"> In order to demonstrate the full power of the LSP-MLP, the same sentences could be processed by the joint DMLP/LSP-MLP systems and stored in a RDB table - as is done in other experiments involving the LSP system (Hirschman et al., 1981).</Paragraph>
    <Paragraph position="1"> Specific SQL-queries can then return the ID-number of the sentence with the relevant information instead of the information itself. If the ID-number is added to the original document as a pseudo-HTML code, the same mechanism as mentioned above can be used to highlight the sentences containing the relevant information. Several variants on this base scheme can be thought of.</Paragraph>
    <Paragraph position="2"> Following the line of research of Sager (Sager et al., 1995a) and Wingert (Wingert et al., 1989), classification codes could already be generated automatically (see also (Lovis et al., 1995)) and presented on the screen next to the original text. But the human encoder would remain responsible for the ultimate selection of the exact codes.</Paragraph>
    <Paragraph position="3"> Another possibility is the creation of &amp;quot;views&amp;quot; or &amp;quot;masks&amp;quot;. HTML files can be generated with &amp;quot;hard coded&amp;quot; instructions to emphasise fixed combinations of semantic labels. Buttons in the menu-page allow to display very rapidly the selected view on the PDS.</Paragraph>
    <Paragraph position="4"> Several experiments for English have already been successfully carried out (?) on the use of &amp;quot;static WWW-technology&amp;quot;. Interesting as well is the cre- null ation of Document Type Definitions (DTD) that associate a particular layout with a specific semantic label (see also (Zweigenbaum et al., 1997)). The DTDs can act as a locally defined view (GUI aspect) on common SGML data (NLP aspect).</Paragraph>
    <Paragraph position="5"> Other potential applications in the medical domain for the DMLP/LSP-MLP combination are e.g., the determination of patient profiles (Borst et al., 1991), quality assurance (Lyman et al., 1991) and extraction of sign/syptom information for medication (Lyman et al., 198.5). Overviews of the possible utilisation in the healthcare area of NLP based systems, irrespective of their theoretical background, can be found in (Baud et al., 1992b) &amp; (Sager et al., 1987, chapter2).</Paragraph>
    <Paragraph position="6"> But before any application of such an extent can be envisaged for Dutch, the words of the dictionary database all have to receive the appropriate semantic label(s). Luckily, this process can be automated. The LSP-team has implemented such routines (Hirschman et al., 1975) but other techniques could be applied as well (see (Habert et al., 1996)).</Paragraph>
    <Paragraph position="7"> From a technical point of view, it would be better to group all the involved software modules (NLP, RDBMS, WWW) on the same platform to optimally exploit the potentialities offered by the combination of the components mentioned. Ultimately, a client/server architecture (separating language specific from domain specific issues and the linguistic aspects from user interface aspects) will be the best architecture for a real life application.</Paragraph>
    <Paragraph position="8"> We can conclude that the application presented above shows the feasibility to integrate Electronic Medical Record (EMR) systems with NLP applications. This is the kernel message of the DOME project (Bouaud et al., 1996) that advocates the use of SGML - and HTML-technology for EMR systems.</Paragraph>
    <Paragraph position="9"> The above presented WWW-application could thus be integrated in such a hypertextuM EMR system.</Paragraph>
    <Paragraph position="10">  ~- .. 7r \] m ..... I' . &amp;quot; M i Rle Edit View Go Bookmarks Options Directory Window Help I ! tdeg 'tio&amp;quot;:IIhttp:// ll e=v'=ug'a='be/'pspyns/tes'&amp;quot; J I ''| i ......... 11 Select a text to process:  Select the semanl~c category: \[multiple selection is ~dlowed\] For afull dC/scrip~on of the categories: see N. Sager, M. Lyman, N.T. Nhan, L J, Tick, Medical Language Processing: Applications to Patient Data Representation and Automatic Encoding, in Methods in Information in Medicine 34 (t/2): 140-157.</Paragraph>
    <Paragraph position="11"> Or go to the next paragraph containing a short definition of the labels (Reprinted from the above, me.nfionad referancal</Paragraph>
  </Section>
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