Heart Disease & Diabetes Prediction using Machine Learning
Keywords:
Machine Learning,, AI algorithms, Heart Attack,Abstract
Over the last decade heart disease is the main reason for death in the world. Almost one person dies of Heart disease about every minute in India alone. In order to lower the number of deaths from heart diseases, there has to be a fast and efficient detection technique. Decision Tree is one of the effective data mining methods till this date. The algorithm used in this project is namely are Decision Tree, Naïve Byes, Support vector machine(SVM), k-nearest neighbours algorithm (KNN), Logistic regression, Random Forests. Heart disease defines several healthcare conditions that are vast in nature which is related to the heart and has many basic causes that affect the entire body.The data set employed in most of the concerned literature is Pima Indian Diabetic Data Set. Early diabetes detection is significant as it helps to reduce the fatal effects of the diabetes. Various machine learning techniques like artificialneural network,principal component, decision trees, genetic algorithms, Fuzzy logic etc. have been discussed and compared. This paper first introduces the basic notions of diabetes and then describes thevarious techniques used to detect it. Anextensive literature survey is then presented with relevant conclusion and future scopes with analysis have beendiscussed
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