Current trends with natural language processing.
Natural Language Processing in the medical domain becomes more and more powerful, efficient, and ready to be used in daily practice. The needs for such tools are enormous in the medical field, due to the vast amount of written texts for medical records. In the authors' point of view, the Electronic Patient Record (EPR) is achieved neither with Information Systems of all kinds nor with commercially available word processing systems. Natural Language Processing (NLP) is one dimension of the EPR, as well as Image Processing and Decision Support Systems. Analysis of medical texts to facilitate indexing and retrieval is well known. The need for a generation tool is to produce progress notes from menu driven systems. The computer systems of tomorrow cannot miss any single dimension. Since 1988, we've been developing an NLP system; it is supported by the European program AIM (Advanced Informatics in Medicine) within the GALEN and HELIOS consortium and the CERS (Commission d'Encouragement á la Recherche Scientifique) in Switzerland. The main directions of development are: a medical language analyzer, a language generator, a query processor, and dictionary building tools to support the Medical Linguistic Knowledge Base (MLKB). The knowledge representation schema is essentially based on Sowa's conceptual graphs, and the MLKB is multilingual from its design phase; it currently incorporates the English and the French languages; it will also continue using German. The goal of this demonstration is to provide evidence of what exists today, what will be soon available, and what is planned for the long term. Complete sentences will be processed in real time, and the browsing capabilities of the MLKB will be exercised. In particular, the following features will be presented: Analysis of complete sentences with verbs and relatives, as extracted from clinical narratives, with special attention to the method of "proximity processing" as developed in our group and the rule based approach to language description to resolve the specific surface language problems as well as the language independent semantic situations. Comparison of results for English, French, and German sentences, showing the commonalities between these languages and, therefore, the re-usable features and the language specific aspects. Generation of noun phrases in English and French, showing the opportunities for translation between these two languages. Application of the analyzer to build a knowledge representation of ICD under the form of conceptual graphs and presentation of the possibilities of a natural language encoding of diagnosis. Strategies for query processing through a sample of abdominal ultrasonography reports, which have been analyzed and stored under the form of conceptual graphs. Feeding in and browsing of the Medical Linguistic Knowledge Base and other Dictionary Building Tools, using the perspective of an international initiative to converge towards a multilingual universal solution, valid for the medical domain. The demonstration platform is Microsoft Windows 4 on a PC, with Microsoft Visual Basic as the GUI and Quintus Prolog as NLP tools language. The same programs were originally developed for Unix-based workstations and are available on multiple platforms under Motif and X11. .
Rassinoux
A M
AM
Faculty of Medicine, Geneva University Hospital, Switzerland.
Michel
P A
PA
Wagner
J
J
Baud
R
R
D005062:European Union; D016347:Medical Records Systems, Computerized / Q000639:trends*; D009323:Natural Language Processing