Classification and Statistics of Endocrine Diseases and Diagnoses Based on Artificial Intelligence

Author

Yan Shuxun ; Wang Ying ; Li Huan ; Li Yun

Author_Institution

Henan Coll. of Traditional Chinese Med., Zhengzhou, China

fYear

2013

fDate

6-7 Nov. 2013

Firstpage

202

Lastpage

207

Abstract

In this paper, we introduce the design and experiments of project for Integrated and Agent Retrieval System to classify domain digital resource of diseases and diagnoses. According to the domain ontology of disease and diagnoses, the modelling, constructing and application of Ontology in this project will service for agent retrieval and knowledge-based management, which present the application of information visualization technology in human interface design by analysis.

Keywords

data visualisation; deductive databases; diseases; information retrieval systems; medical computing; multi-agent systems; ontologies (artificial intelligence); patient diagnosis; pattern classification; statistical analysis; user interfaces; agent retrieval system; artificial intelligence; domain ontology; endocrine diagnosis classification; endocrine diagnosis statistics; endocrine disease classification; endocrine disease statistics; human interface design-by-analysis; information visualization technology; integrated retrieval system; knowledge-based management; Biochemistry; Diseases; Medical diagnostic imaging; Ontologies; Semantics; Visualization; Blast furnace gas; Dust content; Glass fiber; collection efficiency;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems Design and Engineering Applications, 2013 Fourth International Conference on

Conference_Location

Zhangjiajie

Print_ISBN

978-1-4799-2791-3

Type

conf

DOI

10.1109/ISDEA.2013.450

Filename

6843427