Related Experiment Videos
Automatic extraction of linguistic knowledge from an international classification.
R Baud1, C Lovis, A M Rassinoux
1Division d'Informatique Médicale, University Hospital of Geneva, Switzerland. Robert.Baud@dim.hcuge.ch
Studies in Health Technology and Informatics
|June 29, 1999
Summary
This study introduces a rule-based tool for automatic extraction of medical knowledge, creating multilingual lexicons. It addresses the need for computer-readable medical data across languages.
Area of Science:
- Medical Informatics
- Computational Linguistics
- Lexicography
Background:
- Lack of comprehensive, computer-readable medical lexicons, especially multilingual ones.
- Manual extraction of linguistic knowledge is time-consuming and insufficient for broad applications.
- Need for automated methods to build versatile medical lexicons for multiple languages.
Purpose of the Study:
- To develop an intelligent, rule-based tool for automatic knowledge extraction from medical texts.
- To facilitate the creation of multilingual medical lexicons.
- To bridge the gap in computer-readable medical knowledge across different languages.
Main Methods:
- Development of an intelligent rule-based tool.
- Focus on multilingual medical knowledge sources, such as the International Classification of Disease (ICD).
- Utilizing ICD's extensive vocabulary translated into numerous languages.
Main Results:
- Demonstrated an automated approach to extract medical knowledge.
- Enabled the creation of a multilingual medical lexicon by leveraging existing translated resources.
- Provided a foundation for computer-assisted linguistic knowledge acquisition in the medical domain.
Conclusions:
- The developed tool offers an efficient method for building multilingual medical lexicons.
- Automated extraction is crucial for advancing linguistic knowledge acquisition in medicine.
- This approach supports the creation of versatile medical resources for diverse language applications.