Heart disease is the main reason for a huge number of deaths in the world over the last few decades and has evolved as the most life threatening disease. The health care industry is found to be rich in information. So, there is a need to discover hidden patterns and trends in them. For this purpose, data mining techniques can be applied to extract the knowledge from the large sets of data. Many researchers, in recent times have been using several machine learning techniques for predicting the heart related diseases as it can predict the disease effectively. Even though a machine learning technique proves to be effective in assisting the decision makers, still there is a scope for developing an accurate and efficient system to diagnose and predict the heart diseases thereby helping doctors with ease of work. This paper presents a survey of various techniques used for predicting heart disease and reviews their performance.
by G. Niranjana | Dr I. Elizabeth Shanthi "A Survey on Heart Disease Prediction Techniques"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021,
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