Data mining plays a very important role in Health- care industry. Be it in predicting diseases based on symptoms or
predicting the stage / level of severity of any disease, data mining has proved to be very helpful. Healthcare industries collect
huge amounts of data and thus, the use of machine learning saves time and guarantees performance. In this paper we analysed
the various data mining techniques which can be used in the healthcare industry for heart disease prediction and proposed a
system using artificial neural networks for the same. The Proposed System uses 8 medical attributes such as sex, thallium test
results, chest pain type, exang, age, etc., the accuracy and key influencers for the proposed system have been discussed too. The
most preferred supervised learning techniques are decision trees, naïve Bayes and random forest and the analysis for the same
has been done.
