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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. Besides words 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 from 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.

journal_name

Artif Intell Med

journal_title

Artificial intelligence in medicine

authors

Lovis C,Baud R,Rassinoux AM,Michel PA,Scherrer JR

doi

10.1016/s0933-3657(98)00023-2

subject

Has Abstract

pub_date

1998-09-01 00:00:00

pages

201-14

issue

1-2

eissn

0933-3657

issn

1873-2860

pii

S0933-3657(98)00023-2

journal_volume

14

pub_type

杂志文章

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