Fuzzy Clustering and Genetic Algorithm for Clinical Practice Guideline Execution Engines

被引:0
|
作者
Hema, D. [1 ,2 ]
David, Vasantha Kalyani [1 ,2 ]
机构
[1] Avinashilingam Univ, Coimbatore, Tamil Nadu, India
[2] Inst Home Sci & Higher Educ Women, Coimbatore, Tamil Nadu, India
关键词
CPG; Fuzzy c means; GA; OWL; NLP;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The clinical practice guideline (CPG) is used to support the decision system using general practitioner. The patient symptoms are recommended and followed as per CPG. Medical knowledge is framed on the clinical decision making and clinical practice. The NLP is important data source for clinical decision. The NLP system is included in part of speech tagging. Fuzzy c means are used to group the symptoms. The fuzzy membership function is used to find the Fuzzy c means clustering approach to determine the centroid correctly. OWL Language is used to map (onto map) symptoms and disease in the clinical evaluation. The healthcare, semantic web and ontology's for the patients clinical practice is based on CPG. Ontology is potentially integrated with health care. Ontology's are accessed through the user interface and frame work. The gaps between the users requirement is suggested. Genetic Algorithms (GA) via clustering is used for posting the optimization issues. GA provides optimal results when used in complex issues. Genetic Algorithm is optimized for stomach disease prediction as well.
引用
收藏
页码:922 / 925
页数:4
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