HEART FAILURE PREDICTION USING MACHINE LEARNING
Jaya shree
, Megavarshini , Maheshwari , Angel Meriba , Vimala S
Heart Failure is a major issue in the modern society. It presently ranks among the most dangerous illnesses that can affect people, shortening lifespans. The chance of heart disease can be raised by a number of factors, including smoking, body cholesterol levels, a family history of the disease, obesity, high blood pressure, diabetes, and inactivity. To analysis heart failure dataset here we are using machine learning algorithms. Machine learning is a method to predict the target value using input values. The outcomes of this prediction is based on the Naive Bayes (NB), Logistic Regression (LR) and Support Vector Machine (SVM) are introduced for effective forecasting as these machine learning algorithm achieve the best accuracy.
"HEART FAILURE PREDICTION USING MACHINE LEARNING", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.655-663, February-2024, Available :https://tijer.org/TIJER/papers/TIJERB001104.pdf
Volume 11
Issue 2,
February-2024
Pages : 655-663
Paper Reg. ID: TIJER_151045
Published Paper Id: TIJERB001104
Downloads: 000282
Research Area: Science and Technology
Country: Thiruvallur,Chennai, Tamil Nadu, India
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
