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)
Heart disease describes various conditions that affect the heart. One of the heart disease is
cardiac arrest. Cardiac arrest is when the heart comes to a sudden and unexpected end. This is a medical
emergency that, without immediate medical action, will cause sudden cardiac death within minutes.
Nowadays, this disease is among one of the most common serious illest affecting human health. So this disease
should be treated immediately. This project aims to study different machine learning algorithms on the
dataset to predict the possibility of a cardiac arrest. We are using predictive techniques such as ANN, Logistic
regression, Random forest, XGBoost and comparing their accuracy to know which suits best for our data set. In
this project we are taking UCI dataset to perform the analysis.
Keywords:
Cite Article:
"Prediction on cardiac arrest using machine learning algorithms", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 1, page no.d188-d192, January-2023, Available :http://www.ijnrd.org/papers/IJNRD2301323.pdf
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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
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