Prediction and Classification of Heart Disease using AML and Power BI

Debmalya Chatterjee, Saravanan Chandran

2019

Abstract

Machine Learning (ML) is transforming the industries from delivering normal products to deliver intellect products. Large sets of data points are analysed by the computers and the relationship modelling is applied in a predictive way in real time to obtain accurate results. Machine Learning is adopted in healthcare problems for increasing efficiencies, saving money, and saving lives. The cost of medical treatment is reduced and the healthcare processes are optimized throughout the organization with the support of ML. ML improves healthcare delivery and patient health. Machine learning improves diagnosis and treatment options, also empowers individuals to take control of their health. Diagnosis advancements, predictive healthcare, medicines, and helping patients through ML interface produces better results. Heart Disease relates to many numbers of medical complications related to the heart. In recent years, ML has spread its knowledge in every field. In healthcare, the usage of ML has been significantly increased. This research work aims at the prediction of heart disease and classification of heart disease using Machine Learning algorithms. The experimental results are classified into five heart disease stages using values 0, 1, 2, 3, and 4, value 0 for no heart disease and 4 for severe heart disease. The Area Under the Curve (AUC) values depict the accuracy level of the prediction using this proposed model. The results are displayed using the data set in the form of charts that is easy to analyse the number of people having chest pains. The ML analytical report added up in the form of charts or other visuals, the results are reported informatively. This analysis is helpful for doctors and the medical industry for several case studies.

Paper Citation

in Harvard Style

Chatterjee D. and Chandran S. (2019). Prediction and Classification of Heart Disease using AML and Power BI. In Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: NCTA; ISBN 978-989-758-384-1, SciTePress, pages 508-515. DOI: 10.5220/0008381505080515

in Bibtex Style

@conference{ncta19,
author={Debmalya Chatterjee and Saravanan Chandran},
title={Prediction and Classification of Heart Disease using AML and Power BI},
booktitle={Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: NCTA},
year={2019},
pages={508-515},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008381505080515},
isbn={978-989-758-384-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: NCTA
TI - Prediction and Classification of Heart Disease using AML and Power BI
SN - 978-989-758-384-1
AU - Chatterjee D.
AU - Chandran S.
PY - 2019
SP - 508
EP - 515
DO - 10.5220/0008381505080515
PB - SciTePress