Paper Info
Title
Medical Dictionaries For Patient Encoding Systems: A Methodology
Abstract
Medical language is highly compositional and makes extensive use of common roots, especially Latino-Greek roots. Besideswords devoted to common sense, medical language presents some typical characteristics,especially on morphological and semantic aspects of word formation. Morphological decomposition and identification precedes semantic analysis. It is only when these two prerequisites are fulfilled that an attempt to grasp the meaning of a whole expression is made possible. The main aim of the proposed approach is that of coping with 'the lack of coverage of the medical lexical knowledge', in order to help physicians find the correct international classification for diseases (ICD) codes for a written diagnosis. The proposed methodology allows the development of a powerful dynamic dictionary dedicated to natural language processing in the field of diagnoses and narrative procedures. It describes the design of an analyser that can profit fromh a dictionary. The methods used have proved to be efficient for various classifications, s well as for multiple languages, as the system presently supports French, German, English and Dutch for ICD-9 and ICD-10 classifications. (C) 1998 Elsevier Science B.V. All rights reserved.
Year
DOI
Venue
1998
10.1016/S0933-3657(98)00023-2
ARTIFICIAL INTELLIGENCE IN MEDICINE
Keywords
Field
DocType
natural language processing, classifications, knowledge representation
Word formation,Knowledge representation and reasoning,GRASP,Common sense,Computer science,Narrative,Natural language processing,Artificial intelligence,Unified Medical Language System,Machine learning,Medical diagnosis,German
Journal
Volume
Issue
ISSN
14
1-2
0933-3657
Citations 
PageRank 
References 
25
4.55
2
Authors
5
Name
Order
Citations
PageRank
C Lovis18519.90
Robert H. Baud233360.59
A M Rassinoux311720.95
P A Michel4347.70
Jean-Raoul Scherrer511324.96