Heart Disease Prediction and Risk Analysis Using Machine Learning Techniques
Aditya Yadav
, Meet Thakor , Rimsy Dua , Santosh Kumar Singh
Heart disease, Risk factors, Early Detection, Machine Learning, Risk prediction
— Heart disease stands among the major global causes of death because its risk factors include genetic factors alongside hereditary components and environmental variables as well as health-related independent factors. Medical professionals need early detection to generate positive results alongside lowered death rates. The application of machine learning technology has delivered a now substantial advancement in heart disease risk assessment. These predictive models use medical history and testing data along with diagnostic information to detect individuals who are at a high risk while they still show no serious symptoms. Current wearable health devices team up with continuous monitoring systems to collect real-time health data which enhances the development of dynamic personalized prediction models
"Heart Disease Prediction and Risk Analysis Using Machine Learning Techniques ", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 3, page no.b271-b275, March-2025, Available :https://ijsdr.org/papers/IJSDR2503130.pdf
Volume 10
Issue 3,
March-2025
Pages : b271-b275
Paper Reg. ID: IJSDR_301049
Published Paper Id: IJSDR2503130
Downloads: 000113
Research Area: Science All
Country: Mumbai, Maharashtra, India
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
