A PREDICTIVE MODEL FOR THE DIAGNOSIS OF HEART DISEASE WITH THE USE OF MACHINE LEARNING TECHNIQUES
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TextPublisher: Ibafo COMPUTER SCIENCE AND MATHEMATICS 2020Edition: DR. F. A. KASALIDescription: ix; 50 dia, tablesSubject(s): Computer ScienceSummary: Heart diseases have the highest death toll since 2000. Heart disease on its own is basically a deficiency in the heart of living things and there are multiple kinds of heart diseases such as arrhythmia, atherosclerosis, congenital heart defects, coronary artery disease among many others. This study aims to use machine learning techniques ranging from feature selection, principal component analysis, cross-validation and several machine learning algorithms.
Historical data on the distribution of heart disease among patients have been gathered and I acquired this data to be used in this research study. The predictive model for diagnosing heart diseases was developed using several machine learning algorithms.
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Heart diseases have the highest death toll since 2000. Heart disease on its own is basically a deficiency in the heart of living things and there are multiple kinds of heart diseases such as arrhythmia, atherosclerosis, congenital heart defects, coronary artery disease among many others. This study aims to use machine learning techniques ranging from feature selection, principal component analysis, cross-validation and several machine learning algorithms.
Historical data on the distribution of heart disease among patients have been gathered and I acquired this data to be used in this research study. The predictive model for diagnosing heart diseases was developed using several machine learning algorithms.
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