Heart Disease Prediction using Deep Learning and Artificial intelligence

Authors

  • Niharikareddy Meenigea
  • Venkata ravi kiran kolla

Abstract

This study plans to utilize information mining procedures in coronary illness expectation, with improving boundaries to be utilized, so they can be utilized in M2M far off quiet checking reason. KNN is utilized with boundary weighting strategy to further develop precision. Just 8 boundaries are utilized (out of 13 boundaries suggested), since they are straightforward and moment boundaries that can be estimated at home. That's what the outcome shows the precision of these 8 boundaries utilizing KNN calculation are great enough, contrasting with 13 boundaries with KNN, or much other calculations like Guileless Bayes and Choice Tree.

References

kolla, V. (2009). LANE DETECTION SYSTEM USING APPLICATION OF MACHINE LEARNING. Transactions on Latest Trends in Health Sector, 1(1). Retrieved from https://www.ijsdcs.com/index.php/TLHS/article/view/270

Bhatia, V., & Bhatia, G. (2013a). Room temperature based fan speed control system using pulse width modulation technique. International Journal of Computer Applications, 81(5).

Bhatia, V., & Whig, P. (2013b). A secured dual tune multi frequency based smart elevator control system. International Journal of Research in Engineering and Advanced Technology, 4(1), 1163–2319.

Published

2013-08-17

How to Cite

Meenigea , N., & kolla, V. ravi kiran. (2013). Heart Disease Prediction using Deep Learning and Artificial intelligence. International Journal of Statistical Computation and Simulation, 5(1). Retrieved from https://journals.threws.com/index.php/IJSCS/article/view/150

Issue

Section

Articles