Classification of Correlation Patterns Based on electrocardiogram Data of Heart Defects Using the Pearson Correlation Coefficient Method

Abstract

This study was conducted to map the relationship between a symptom and the type of heart disease, based on the results of the electrocardiogram medical record data. The purpose of this study was to apply a symptom correlation pattern based on electrocardiogram data of heart abnormalities. Where the results of this study produce values that determine symptoms that have a very close relationship with the type of heart disorder, and make an analysis to diagnose normal and abnormal heart disorders using the Pearson Correlation Coefficient (PCC) approach. The results show that the relationship between symptoms has a very strong relationship. dominant with normal heart defects is the relationship between AV conduction duration and other symptoms because the relationship between AV conduction duration and other symptoms has a very strong average level of association. symptoms also have a strong average level of association, while the relationship between other symptoms appears to have a moderate relationship and does not even have any relationship with someone who is identified as having a heart abnormality diagnosis (abnormal) and normal heart

Keywords

• keyword: electrocardiogram, pearson correlation coefficient, symptoms, diagnosis, heart disease