Heart Disease Prediction using CNN, Deep Learning model |
Author(s): |
| Poonam Vengurlekar , Shah and Anchor Kutchhi Engineering College; Swati Nadkarni, Shah and Anchor Kutchhi Engineering College; Dr. Bhavesh Patel, Shah and Anchor Kutchhi Engineering College |
Keywords: |
| Cleveland Heart Disease Database, Decision Trees, Random forest, Hybrid algorithm, Machine learning |
Abstract |
|
Heart disease is one of the most serious health threat growing among worldwide, for which mortality rate around the world is very high. Early detection of heart disease could save many lives, accurate detection of heart disease is crucial among the health care persons through regular clinical data and its analysis. Artificial intelligence is the effective solution for decision making and accurate heart disease predictions. Medical industry showing enormous development in using information technology, in which artificial intelligence play major role. In the proposed work, deep learning based approach on heart disease is done on Cleveland dataset. However existing studies are handled in Machine learning technique. The proposed work detects heart disease based in Convolutional Neural Networks. Experimental results shows our proposed work achieves high level of accuracy in prediction of heart disease. |
Other Details |
|
Paper ID: IJSRDV8I100207 Published in: Volume : 8, Issue : 10 Publication Date: 01/01/2021 Page(s): 469-473 |
Article Preview |
|
|
|
|
