A combinatorial approach to conceptual graph projection checking

Automated Coding of Patient Discharge Summaries Using Conceptual Graphs

Methods of Information in Medicine ◽

10.1055/s-0038-1634611 ◽

1995 ◽

Vol 34 (04) ◽

pp. 345-351 ◽

Cited By ~ 11

Author(s):

A. Burgun ◽

L. P. Seka ◽

D. Delamarre ◽

P. Le Beux

Keyword(s):

Natural Language ◽

Patient Discharge ◽

Natural Language Understanding ◽

Assessment Procedure ◽

Coding System ◽

Language Understanding ◽

Processing Scheme ◽

Automated Coding ◽

Conceptual Graph ◽

Discharge Summaries

Abstract:In medicine, as in other domains, indexing and classification is a natural human task which is used for information retrieval and representation. In the medical field, encoding of patient discharge summaries is still a manual time-consuming task. This paper describes an automated coding system of patient discharge summaries from the field of coronary diseases into the ICD-9-CM classification. The system is developed in the context of the European AIM MENELAS project, a natural-language understanding system which uses the conceptual-graph formalism. Indexing is performed by using a two-step processing scheme; a first recognition stage is implemented by a matching procedure and a secondary selection stage is made according to the coding priorities. We show the general features of the necessary translation of the classification terms in the conceptual-graph model, and for the coding rules compliance. An advantage of the system is to provide an objective evaluation and assessment procedure for natural-language understanding.

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A Combinatorial Approach to Some Sparse Matrix Problems.

10.21236/ada131387 ◽

1983 ◽

Cited By ~ 21

Author(s):

S. Thomas McCormick

Keyword(s):

Sparse Matrix ◽

Combinatorial Approach ◽

Matrix Problems

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Combinatorial Approach to the Isolation of Human Antibody Fragments and Peptides to Breast Carcinomas

10.21236/ada384093 ◽

1999 ◽

Author(s):

Susan L. Deutscher

Keyword(s):

Antibody Fragments ◽

Human Antibody ◽

Combinatorial Approach ◽

Breast Carcinomas

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Targeting Strategies for Human Immunodeficiency Virus: A Combinatorial Approach

Mini-Reviews in Medicinal Chemistry ◽

10.2174/1389557511209030236 ◽

2012 ◽

Vol 12 (3) ◽

pp. 236-254 ◽

Cited By ~ 6

Author(s):

S. K. Saxena ◽

A. Gupta ◽

K. Bhagyashree ◽

R. Saxena ◽

N. Arora ◽

...

Keyword(s):

Human Immunodeficiency Virus ◽

Combinatorial Approach ◽

Immunodeficiency Virus

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A FORMALISM FOR REPRESENTING AND REASONING WITH LINGUISTIC INFORMATION

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems ◽

10.1142/s021848850200148x ◽

2002 ◽

Vol 10 (03) ◽

pp. 281-307 ◽

Cited By ~ 4

Author(s):

TRU H. CAO

Keyword(s):

Artificial Intelligence ◽

Fuzzy Logic ◽

Natural Language ◽

Functional Relation ◽

Computing With Words ◽

Conceptual Graphs ◽

Graph Language ◽

Conceptual Graph ◽

Knowledge Representation Language ◽

Representation Language

Conceptual graphs and fuzzy logic are two logical formalisms that emphasize the target of natural language, where conceptual graphs provide a structure of formulas close to that of natural language sentences while fuzzy logic provides a methodology for computing with words. This paper proposes fuzzy conceptual graphs as a knowledge representation language that combines the advantages of both the two formalisms for artificial intelligence approaching human expression and reasoning. Firstly, the conceptual graph language is extended with functional relation types for representing functional dependency, and conjunctive types for joining concepts and relations. Then fuzzy conceptual graphs are formulated as a generalization of conceptual graphs where fuzzy types and fuzzy attribute-values are used in place of crisp types and crisp attribute-values. Projection and join as basic operations for reasoning on fuzzy conceptual graphs are defined, taking into account the semantics of fuzzy set-based values.

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