PP-032 Prediction of Cholesterol Level in Patient with Myocardial Infarction Based on Data Mining Methods

The retrospective data set including gender, age, weight, height, pulse, glucose, creatinine, triglyceride, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) were employed for predicting the cholesterol level.

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Bibliographic Details
Published inThe American journal of cardiology Vol. 115; p. S111
Main Authors Colak, Cengiz, Colak, Cemil, Ermiş, Necip, Erdil, Nevzat, Ozdemir, Ramazan
Format Journal Article
LanguageEnglish
Published New York Elsevier Inc 16.03.2015
Elsevier Limited
Subjects
Cardiovascular
Cardiovascular disease
Cholesterol
Data mining
Datasets
Methods
Neural networks
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Summary:The retrospective data set including gender, age, weight, height, pulse, glucose, creatinine, triglyceride, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) were employed for predicting the cholesterol level.
ISSN:0002-9149
1879-1913
DOI:10.1016/j.amjcard.2015.01.388