INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Cardiovascular diseases, including heart attacks, remain one of the leading causes of mortality worldwide. Early detection and accurate classification of individuals at risk of experiencing a heart attack are crucial for taking preventive measures. In this research paper, we explore various machine-learning algorithms for heart attack prediction and classification. Leveraging a dataset comprising diverse parameters, we utilize various machine-learning techniques. Our study aims to develop an efficient predictive model capable of identifying individuals susceptible to heart attacks and effectively classifying them. Through comprehensive experimentation and evaluation, we assess the performance of these models, thereby contributing to the advancement of cardiovascular health management.
"Machine Learning Approaches to Heart Attack Risk Detection and Classification ", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 3, page no.a679-a683, March-2024, Available :http://www.ijnrd.org/papers/IJNRD2403074.pdf
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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
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