Heart disease prediction using Hybrid KNN
Shaik Reenadh
, Sreshta , Naveena , Suma Manvika , Shaik Reenadh
In this study, heart disease is anticipated using machine learning. Machine learning plays a crucial role in recognizing
motor illnesses like heart diseases if such data is predicted in advance. This gives clinicians the insight they need to treat each
patient individually. In our project, we will derive various insights from the dataset that helps us to analyze the weightage of
individual features and how they are related to one another. We have used a new algorithm called modified knn (mknn) and
compared it with existing algorithms like k-nearest neighbours support vector classifier. The healthcare industry collects a
tremendous amount of data, but not all the data finds hidden patterns and can help in making valuable decisions.
"Heart disease prediction using Hybrid KNN", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 10, page no.c315-c318, October-2024, Available :https://ijnrd.org/papers/IJNRD2410241.pdf
Volume 9
Issue 10,
October-2024
Pages : c315-c318
Paper Reg. ID: IJNRD_301400
Published Paper Id: IJNRD2410241
Downloads: 00019
Research Area: Science and Technology
Country: Nizamabad, Telangana, 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
