Electronic Health Record to Predict a Heart Attack Used Data Mining With Naive Bayes Method

Johanes Fernandes Andry

Abstract


Acute Myocardial Infaction (Heart Attack) is one of the deadliest diseases patient worlds. The cases related to Cardiovascular diseases (CVD) are including stroke, hypertension, and heart attack. To resolving Cardiovascular disease (CVD) is to evaluate large scores of datasets, compare and mine for information that can be used to predict, prevent, manage and threat chronic diseases such as heart attacks. Data minings are technologies or tools of big data in mining the voluminous datasets for information. Method used naïve Bayes classification because that method can determine target which can be used to answer some questions like whether the patient has the potential for heart disease. After data analyst, authors can use data to Electronic Health Record (EHR). 

Keywords


Heart Attack, Data Mining, Naïve Bayes, Electronic Health Record, Cardiovascular diseases

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DOI: http://doi.org/10.11591/ijict.v10i3.pp%25p

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