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Paper Title : Heart Disease Prediction By Using Machine Learning

ISSN : 2395-1303
Year of Publication : 2022
10.5281/zenodo.7238950

Authors: B. Prathyusha, K. Sai Mahima, M. Preethi, M. Supraja

         


Abstract
One of the most important issues facing the globe today is heart disease. Hybrid machine learning (ML) has demonstrated its ability to effectively support decision-making and prediction from the vast amounts of data generated by the healthcare sector and hospitals. Only a few research have used machine learning to predict cardiac disease. The current technique for predicting heart disease improves medical care while costing less. Several combinations of the prediction model are suggested, each with a particular feature.

Reference
[1] Goel R Heart Disease Prediction Using Different Machine Learning Algorithms. [2] Predicting the Risk of Heart Failure With EHR Sequential Data Modelling, Jin B, Che C, Liu Z, et al(2014). [3] Comparing five alternative iterative reconstruction techniques for computed tomography in a ROC analysis. [4] Design and Implementation of Heart Disease Prediction Using Naive Bayesian, Repaka AN, Ravikanti SD, and Franklin RG (2019). [5] Fast rule-based heart disease prediction via associative classification mining by Lakshmi KP, Prasanna Lakshmi K, and Reddy CRK(2015). [6] Comparative Analysis between Nave Bayes Algorithm, Al-Bayaty BFZ, Zopon Al-Bayaty BF, Bharati Vidyapeeth University, et al(2016).
Keywords
— Random Forest Tree, Machine Learning Techniques, and Cardiovascular Disease Prediction.