Prediction of mortality in patients with cardiovascular disease using data mining methods

Healthcare information systems store a huge amount of patient data, so the trend of the use of data mining in healthcare is on the rise. Heart and blood vessel diseases are a leading cause of mortality both worldwide and here in Bosnia and Herzegovina, and prevention, surveillance and treatment are...

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Bibliographic Details
Published in2020 19th International Symposium INFOTEH-JAHORINA (INFOTEH) pp. 1 - 4
Main Authors Imamovic, Damir, Babovic, Elmir, Bijedic, Nina
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2020
Subjects
Cardiovascular diseases
Data mining
decision tree
Decision trees
healthcare analytics
logistic regression
Logistics
Neural networks
predicting
Predictive models
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Summary:Healthcare information systems store a huge amount of patient data, so the trend of the use of data mining in healthcare is on the rise. Heart and blood vessel diseases are a leading cause of mortality both worldwide and here in Bosnia and Herzegovina, and prevention, surveillance and treatment are of great public health importance. Based on data on patients with cardiovascular disease, collected from 2011 to 2017 at Mostar Hospital, models for mortality prediction using techniques for data tree mining, neural network and logistic regression are presented. The aim of this research is to compare the effectiveness of these methods in modeling the effectiveness of predicting mortality in patients with cardiovascular disease.
DOI:10.1109/INFOTEH48170.2020.9066297