HEART DISEASE PREDICTION USING BIO- INSPIRED ALGORITHMS

Abstract

Heart related diseases or Cardiovascular Diseases (CVDs) are the main reason for a
huge number of death in the world over the last few decades and has emerged as the
most life-threatening disease, not only in India but in the whole world. So, there is a
need of reliable, accurate and feasible system to diagnose such diseases in time for
proper treatment. Machine Learning algorithms and techniques have been applied to
various medical datasets to automate the analysis of large and complex data. Many
researchers, in recent times, have been using several machine learning techniques to
help the health care industry and the professionals in the diagnosis of heart related
diseases. This paper presents a survey of various models based on such algorithms
and techniques andanalyze their performance. Models based on supervised learning
algorithms such as Support Vector Machines (SVM), K-Nearest Neighbour (KNN),
NaïveBayes, Decision Trees (DT), Random Forest (RF) and ensemble models are
found very popular among the researchers.