Survival Analysis of Heart Failure Patients Using Machine Learning

dc.contributor.authorHuda, S.M Rakibul
dc.contributor.authorHasan, Nabid
dc.contributor.authorAhsan, Fahad
dc.date.accessioned2022-07-30T05:57:39Z
dc.date.available2022-07-30T05:57:39Z
dc.date.issued2022-01-13
dc.description.abstractIn modern days heart attack has become a major disease all over the worldwhich is causing huge number of death. Heart attack at early age is a greater risk factor for the people of south Asia than the other regions. It is really hard to predict the stage of a heart attack patient quickly and successfully, because it need a long lime experience and passionate knowledge. Medical industries has a large amount of data which can be used to make effective decision with all the concealed information. With the help of effective decision making and few excellent data mining technique like Logistic Regression, Decision Tree, we will able to predict heart attack patients situation or stage quickly. We used four algorithm in our system those are Random forest classifier, Decision tree, Logistic regression, Support vector machine. Our final model accuracy is 92% where the algorithm is Support Vector Machine(SVM).
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/8367
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/8367
dc.language.isoen_US
dc.publisher©Daffodil International University
dc.sourceDIU Institutional Repository
dc.subjectMachine learning
dc.subjectHeart failure
dc.subjectHeart attack
dc.titleSurvival Analysis of Heart Failure Patients Using Machine Learning
dc.typeOther

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