Research Article
Semantic Doctor Assistant: An Ontology-based Disease Classification in Biomedicine
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 127 - Issue 2 |
| Published: October 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 },
year = { 2015 },
volume = { 127 },
number = { 2 },
pages = { 1-4 },
doi = { 10.5120/ijca2015906320 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2015
%A Yaman Kannot
%A Mohamed Kholif
%A Amani A. Saad
%T Semantic Doctor Assistant: An Ontology-based Disease Classification in Biomedicine%T
%J International Journal of Computer Applications
%V 127
%N 2
%P 1-4
%R 10.5120/ijca2015906320
%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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