2026-05-01T09:10:07Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/5005 2021-12-13T04:43:44Z 1582963302567:1597824273898 user-ucsy

Extraction of Frequent Patterns from Diabetes Cluster Win, Myint Swe Lai Phyu, Win Lei Lei Data mining is the process of discoveringinteresting knowledge, such as patterns,associations, changes, anomalies and significantstructures, from large amounts of data stored indatabases, data warehouses, or other informationrepositories. In this paper, we have proposed anefficient approach for the extraction of significantpatterns from the patients database for diabetesprediction. The diagnosis of diseases is a significantand tedious task in medicine. To facilitate thediagnosis process, the effort to utilize knowledge andexperience of numerous specialists and clinicalscreening data of patients collected in databases isconsidered a valuable option. The patients databaseis clustered using the KMIX clustering algorithm,which will extract the data relevant to diabetes fromthe database. Subsequently the frequent patterns aremined from the extracted data, relevant to diabetes,using the MAFIA algorithm. Then the significantpatterns to diabetes diagnosis are chosen from thesefrequent patterns. These patterns can be used toapply in the healthcare system. 2010-12-16 http://hdl.handle.net/20.500.12678/0000005005 https://meral.edu.mm/records/5005