What is it about?
The paper deals with machine learning techniques to build an efficient heart disease prediction system. Such system shall be quite useful in low and middle income group countries which face an acute shortage of doctors. The prediction system monitors the vital parameters of the patient to decide if the patient is at the risk of heart disease. The paper discusses the use of bagging and boosting techniques in improving the performance of machine learning based heart disease prediction system .
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Why is it important?
This work opens up a bright chance of improving healthcare opportunities worldwide. Heart diseases are the most important reason of deaths. Early diagnosis is an efficient way to reduce mortality. The heart disease prediction system shall help in saving lives. These are easily affordable and easily accessible to people living in rural places also.
Perspectives
This work aims at providing affordable and easily accessible healthcare facilities to the people living in rural areas.
Ekta Maini
Dayananda Sagar University
Read the Original
This page is a summary of: Improving the performance of heart disease prediction system using ensembling techniques, January 2021, American Institute of Physics,
DOI: 10.1063/5.0036478.
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