DocumentCode :
3272369
Title :
The recommendation of medicines based on multiple criteria decision making and domain ontology — An example of anti-diabetic medicines
Author :
Chen, Rung-cillng ; Jiun-Yao Chiu ; Cho-Tsan Bau
Author_Institution :
Dept. of Inf. Manage., Chaoyang Univ. of Technol., Taichung, Taiwan
Volume :
1
fYear :
2011
fDate :
10-13 July 2011
Firstpage :
27
Lastpage :
32
Abstract :
A recommendation system can help user to make requirement analysis and to recommend better decision from much complex information. This research is concentrated on medical prescription recommendation. According to the statistics of Department of Health, diabetes was the top ten of death in Taiwan. Therefore, developing an effective treatment for diabetes is very important. The purpose of this study is to develop a decision support system to assist a doctor to make more appropriate decision in selecting drugs. We first built the ontology of diabetic knowledge and compute medication by multiples criteria decision making method (MCDM). The entropy was used to compute data of patient´s history and then take this result to integrate medicine knowledge ontology to list appropriate medications. Finally, more suitable medications are recommended to doctors. Primary experiments proof our method is useful.
Keywords :
decision making; decision support systems; drugs; medical computing; medical information systems; ontologies (artificial intelligence); recommender systems; Department of Health; MCDM; Taiwan; anti-diabetic medicines; decision support system; domain ontology; drug selection; medicine knowledge ontology; medicine recommendation; multiple criteria decision making; recommendation system; requirement analysis; Hardware design languages; Medical services; Nickel; Ontologies; Sorting; Sugar; Entropy; Multiple Criteria Decision Making; Ontology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
Conference_Location :
Guilin
ISSN :
2160-133X
Print_ISBN :
978-1-4577-0305-8
Type :
conf
DOI :
10.1109/ICMLC.2011.6016682
Filename :
6016682
Link To Document :
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