HEART DISEASE PREDICTION USING MACHINE LEARNING

Tirtharaj Tamang

Heart Disease is one of the most significant causes of mortality in today’s world.

Across the globe, cardiovascular illnesses are now among the leading causes of death. This worrying problem has been greatly exacerbated by changes in eating, working, and lifestyle patterns in both developed and developing countries worldwide. Early identification of the first symptoms of cardiovascular disorders and ongoing medical care can assist lower the number of patients who are becoming sicker and ultimately the death rate. The number of heart disease cases is rising quickly every day, making it crucial and worrisome to anticipate any such illnesses in advance. This di- agnosis is a challenging task that requires accuracy and efficiency. The study article primarily focuses on identifying patients who has given a vari- ety of medical characteristics, are more likely to suffer heart disease. Using the patient's medical history, we developed a heart disease prediction algorithm to determine the likelihood of a heart disease diagnosis. Utilising various machine learning methods, including logistic regression and KNN, we were able to predict and categorise the patient with heart disease. A very useful method was employed to control the model's ability to increase any person's heart attack prediction accuracy.

Published Paper   E-Certificate

"HEART DISEASE PREDICTION USING MACHINE LEARNING ", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.a255-a258, February-2024, Available :https://tijer.org/TIJER/papers/TIJER2402031.pdf

Volume 11 Issue 2, February-2024

Pages : a255-a258

Paper Reg. ID: TIJER_151228

Published Paper Id: TIJER2402031

Downloads: 000292

Research Area: Science and Technology

Country: Paschim Bardhman, West Bengal, India

Published Paper PDF: https://tijer.org/TIJER/papers/TIJER2402031

Published Paper URL: https://tijer.org/TIJER/viewpaperforall?paper=TIJER2402031

DOI: http://doi.one/10.1729/Journal.37898

ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: TIJER (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition