A Machine Learning Approach For Cardiovascular Stroke Prediction System
Chikkireddy Sri Ravali
, M Subrahmanyeswara Rao , V Anil Santosh
Artificial intelligence, machine Learning, cardiovascular prediction system
Over the past few decades, cardiovascular diseases have surpassed all other causes of death as the main killers in industrialized, underdeveloped, and developing nations. Early detection of heart conditions and clinical care can lower the death rate. Based on the patient's various cardiac features, we proposed a model for forecasting heart disease and identifying impending heart disease using machine learning techniques such logistic regression, SVM, Multinomial Nave Bayes, Random Forest, and Decision Tree. In most cases, input is received through numerical data of various parameters, and output findings are generated in real-time, predicting whether or not the patient has a disease. We'll use a variety of supervised machine learning methods before deciding which one is best for the model. Existing systems rely on classical deep learning models, which are inefficient and imprecise. They aren't as accurate as the proposed model and take a little longer to process.
"A Machine Learning Approach For Cardiovascular Stroke Prediction System", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 10, page no.b865-b871, October-2024, Available :https://ijnrd.org/papers/IJNRD2410193.pdf
Volume 9
Issue 10,
October-2024
Pages : b865-b871
Paper Reg. ID: IJNRD_301330
Published Paper Id: IJNRD2410193
Downloads: 00024
Research Area: Science and Technology
Country: Rajamundry , Andra Pradesh , India
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave
