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Machine Learning Based Hybrid Technique For Heart Disease Prediction

200.00 160.00

Name of writers /editors :

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Saurav Negi, Minakshi Memoria, Rajesh Kumar, Kapil Joshi

978-93-5857-053-3

53

6.38x9.02

Paperback

Nitya Publications, Bhopal

First

-20%

Machine Learning Based Hybrid Technique For Heart Disease Prediction

200.00 160.00

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Description

The medicinal services industry contains large measure of information. This large measure of information, the infection is frequently distinguished, anticipated, or might be relieved. An enormous danger to humanity is brought about by infections like coronary illness, malignant growth, tumor and so forth. In this paper, we attempt to concentrate on coronary illness forecast, utilizing AI methods, coronary illness is regularly anticipated.  The information like pulse, hypertension, diabetes, cigarette smoking is taken as information and afterward these highlights are displayed for forecast.

The calculations like K-nearest neighbour, Random Forest and Decision tree are used. We have also proposed a hybrid model of combining Decision Tree and Random Forest. The precision of the model is to investigate utilizing every one of the calculations. At that point with the more exactness is taken as a result of the model for anticipating the daringness infection.

The UI is designed to get user’s input parameter to predict the heart disease, for which we have used a hybrid model of Random Forest and Decision Tree.

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