Cardiac Studies Diagnostic Data Informative Features Investigation based on Cumulative Frequency Analysis

ABSTRACT

The development of information technology in the modern world affects the public health sector on the one hand and accumulates enormous amounts of data on the other hand. The global COVID-19 pandemic has contributed to the digitalization of healthcare. Heart disease is a global problem that causes death worldwide. Therefore, this study proposes a model for determining the information content of signs of diagnostic data of heart diseases based on the cumulative frequency method. The software implementation of the model has been completed. A database of 303 patients, consisting of 14 attributes, was used for the experiments. As a result of the model's work, the features with the most significant information content were identified. The study is promising and can apply diagnostic models in public health practice. ©2022 Copyright for this paper by its authors.