2026-06-26T19:18:59Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/4001 2021-12-13T08:07:13Z 1582963302567:1597824273898 user-ucsy

Prediction of Significant Heart Attack Patterns Using Clustering Algorithm Han, Aye Mya This system presents an efficient approachfor discovering significant patterns from the heartdisease database for heart attack prediction. Theheart disease data warehouse is clustered using Kmeansclustering algorithm to extract related data.The primary intent of the system is to design anddevelop an efficient approach for extractingpatterns, which are significant to heart attack, fromthe heart disease database. The diagnosis ofdiseases is a significant and tedious task inmedicine. The detection of heart disease fromvarious factors or symptoms is a multi-layeredissue which is not free from false presumptionsoften accompanied by unpredictable effects. Thusthe effort to utilize knowledge and experience ofnumerous specialists and clinical screening data ofpatients collected in databases to facilitate thediagnosis process is considered a valuable option.The proposed system aims to utilize the data miningtechniques: clustering and frequent pattern mining. 2009-12-30 http://hdl.handle.net/20.500.12678/0000004001 https://meral.edu.mm/records/4001