Title :
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
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;
Conference_Titel :
Intelligent Systems Design and Engineering Applications, 2013 Fourth International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-1-4799-2791-3
DOI :
10.1109/ISDEA.2013.450
