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Semantic Doctor Assistant: An Ontology-based Disease Classification in Biomedicine

by Yaman Kannot, Mohamed Kholif, Amani A. Saad
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 127 - Number 2
Year of Publication: 2015
Authors: Yaman Kannot, Mohamed Kholif, Amani A. Saad
10.5120/ijca2015906320

Yaman Kannot, Mohamed Kholif, Amani A. Saad . Semantic Doctor Assistant: An Ontology-based Disease Classification in Biomedicine. International Journal of Computer Applications. 127, 2 ( October 2015), 1-4. DOI=10.5120/ijca2015906320

@article{ 10.5120/ijca2015906320,
author = { Yaman Kannot, Mohamed Kholif, Amani A. Saad },
title = { Semantic Doctor Assistant: An Ontology-based Disease Classification in Biomedicine },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 127 },
number = { 2 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume127/number2/22698-2015906320/ },
doi = { 10.5120/ijca2015906320 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:18:47.558810+05:30
%A Yaman Kannot
%A Mohamed Kholif
%A Amani A. Saad
%T Semantic Doctor Assistant: An Ontology-based Disease Classification in Biomedicine
%J International Journal of Computer Applications
%@ 0975-8887
%V 127
%N 2
%P 1-4
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Human disease data is a cornerstone of biomedical research for diseases’ classification and recommended treatments so; there is a significant need for a standardized representation of human diseases and an efficient algorithm for retrieving information from it. The Semantic Doctor Assistant (SDA) has been designed to help doctors to find proper information about a specific disease using semantic web technology rather than other simple keyword-based search. A preliminary usability study has been done to evaluate the system by measuring user’s satisfaction through a statistical analysis of surveys. This study would measure the relevance of the information retrieved for each search query and how the system is important in the field of medicine and how it will help academic doctors in their research and non-academic doctors in their work.

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Index Terms

Computer Science
Information Sciences

Keywords

Semantic Web Biomedicine Classification Spreading Activation

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