A Novel Approach to Predict Heart Disease |
Author(s): |
| Dayashankar Yadav , NIET; Amit Singh, NIET; Ankush Gupta, NIET; Amrit Suman, NIET; Kumud Saxena, NIET |
Keywords: |
| Machine Learning, Heart Disease, Naïve Bayes, Decision Tree, Neural Network, SVM and Deep Learning |
Abstract |
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According to a recent survey by WHO Organization every year 17.5 million people die each year. It shall increase to 70 million by the year 2030. The medical professionals that have been working in the field of heart disease have their own limitations and they can also save the lives of many people by predicting the chances of heart rate disease up to 65% accuracy. Seeing the current epidemic scenario doctors need a support system for better and precise prediction of heart diseases. Machine Learning opens many possible doors for better prediction of heart related diseases. Paper provides a lot of information about state of art methods in Machine learning and deep learning. An analytical comparison has been provided to help the new researchers working in this field. |
Other Details |
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Paper ID: IJSRDV9I50147 Published in: Volume : 9, Issue : 5 Publication Date: 01/08/2021 Page(s): 141-143 |
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