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Title |
Deep Insight into Diabetic Data with the Help of Association Rule Mining |
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Author |
Adil Aziz, Miss Asma Sajid, Shahbaz Ahmad |
| Citation |
Vol. 26 No. 8 pp. 55-60 |
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Abstract |
Diabetes is most emerging chronic disease in Pakistan as well as around the globe. It may be in form of insulin or glycogen but both forms are hazardous for patients. A decades before diabetic patients were normally mature person whose age range was forty five to onward. But now day youngsters are also indulging in it. Diabetes is associated with mental sickness and strain while these attributes varies from culture to culture and race to race through the world. Developing countries are normally facing major issues like health and poverty along with less financial sources. Whereas most of the people are living nonstandard life and always facing trouble and tension to run their daily lives. Poverty, tension, stress and strain are home hub for diabetes. Data mining technique is very useful for retrieving the association of multiple attributes in a given massive database. In this way we can identify the major attribute among the millions of records which cause the occurrence of diabetic. |
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Keywords |
Diabetic, Association Rule, Data Mining, Apriori |
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