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A Survey On Bridging Vocabulary Gap In Healthcare With Ontology Support

Author(s):

J.U.Paruvatha Kumari , K.S.R. COLLEGE OF ENGINEERING; R.Velumani, K.S.R.COLLEGE OF ENGINEERING; S.Nithyakalyani, K.S.R.COLLEGE OF ENGINEERING

Keywords:

Ontology, Global Learning, Local mining, Question and Answer (QA)

Abstract

Internet is served as a diagnosis tool to facilitate patient-doctor communication. Online health services are deployed to provide remote medical assistance. Community based health services supports automatic disease inference identification for online health seekers. Question and Answer (QA) sessions are suffered with the vocabulary gap and incomplete information. Deep learning scheme is applied to infer the possible diseases using Question and Answer data values. Global learning component is used to mine the discriminant medical signatures from raw features. In local mining raw features and their signatures are updated into the input layer and hidden layer. This paper presents a survey on medical terminology based ontology for improving the relationship in word and detecting diseases.

Other Details

Paper ID: IJSRDV3I70338
Published in: Volume : 3, Issue : 7
Publication Date: 01/10/2015
Page(s): 758-762

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