What is it about?

Machine learning( ML) approach to solve the impact of HRV parameters and its cardiac diseases prediction. The HRV parameters are justified here with the help of intra and inter selection group (IIS)theory which is unique characteristic of the paper. The accuracy is just to be obtained but why it is high and because of which parameter it is high is explained here.

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Why is it important?

The machine learning model is good for obtaining highly accurate results. But this paper has unique labeling for HRV parameters and added parameters. The cardiac disease prediction should be seen to revive around individual features. The impact of individual features is important to look beyond ML model results as a researcher.


Writing this with coauthor has been immensely helped to write pinpoint result analysis with ML model . Random Forest as a classifier has been proved to highly accurate classifier amongst another complex data set.

Er Hemant Pasusangai Kasturiwale
Thakur College of Engineering and Technology

Read the Original

This page is a summary of: BioSignal modelling for prediction of cardiac diseases using intra group selection method, Intelligent Decision Technologies, March 2021, IOS Press,
DOI: 10.3233/idt-200058.
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