Machine Learning Methods in Detecting Heart Related Diseases
DOI:
https://doi.org/10.53469/jrse.2025.07(01).13Keywords:
Cardiovascular Diseases, Support Vector Machines, K - Nearest Neighbour, Naïve Bayes, Decision TreeAbstract
Cardiovascular illnesses, often known as heart - related disorders or CVDs, have been the leading cause of mortality worldwide in recent decades and are now the most serious illness, not just in India but around the world. Therefore, a system that is dependable, accurate, and workable is required to identify these illnesses in time for appropriate treatment. Large - scale and sophisticated data processing has been automated by using machine learning techniques and algorithms to a variety of medical datasets. Recently, a number of researchers have started employing various machine learning approaches to assist the medical community and experts in the detection of heart - related illnesses. An overview of several models built using these methods and algorithms is presented in this work.
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