Heart stroke prediction using machine learning algorithms

Dr.V.Madhuri , Popuri Charan , Shaik Samivunnisa , Tumula Sai Prakash Chari , Pasupuleti Viswa Sai

Heart Stroke Prediction, Machine Learning, Deep Learning, Random Forest, SHAP Interpretability

The project aims to develop a predictive model capable of reliably predicting an individual patients' risk of heart disease according to a set of specific medical characteristics. The objective is thus to enable timely diagnosis and possible intervention for improved patient outcomes and efficiencies within a healthcare system. Such a project includes the data analysis of heart disease dataset of the UCI Machine Learning Repository with Python and Jupyter Notebook. There is data manipulation using the libraries like numpy, pandas, and sklearn.model_selection, to split the dataset into training and test sets, and using Flask as a lightweight backend framework in handling Web requests and returning templates. Predictive models Logistic regression, KNN, random forest, and decision tree will be implemented to test the presence of heart disease based on different medical attributes. In case of heart disease for the subject, precautionary measures and signs of heart stroke are advised and if not, he/she is given warning signs of a heart stroke and preventive measures.

Published Paper   E-Certificate

"Heart stroke prediction using machine learning algorithms", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 3, page no.a697-a707, March-2025, Available :https://ijsdr.org/papers/IJSDR2503082.pdf

Volume 10 Issue 3, March-2025

Pages : a697-a707

Paper Reg. ID: IJSDR_300915

Published Paper Id: IJSDR2503082

Downloads: 000141

Research Area: Science and Technology

Country: -, -, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2503082

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2503082

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

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