Heart Disease Prediction Using Machine Learning.

EasyChair Preprint no. 9460

Abstract

Heart disease prognosis has become one of the most difficult challenges in

the medical sector in recent years. In the modern period, about one person

dies from heart disease every minute. In the realm of healthcare, data

science is critical for analysing massive amounts of data. Because predicting

cardiac illness is a difficult undertaking, it is necessary to automate the

process in order to avoid the risks connected with it and to inform the patient

well in advance. This research takes use of the kaggal UCI machine learning

repository's heart disease dataset.

Keyphrases: MultilayerPerceptron(MLP), NaïveBayes(NB), RandomForest, SupportVectorMachine(SVM)

@Booklet{EasyChair:9460,
  author = {Sharad Chand Bind and Pawan Kumar Pradhan},
  title = {Heart Disease Prediction Using Machine Learning.},
  howpublished = {EasyChair Preprint no. 9460},

  year = {EasyChair, 2022}}