JOURNAL ARTICLE

Heart disease prediction model with k-nearest neighbor algorithm

Tssehay Admassu Assegie

Year: 2021 Journal:   International Journal of Informatics and Communication Technology (IJ-ICT) Vol: 10 (3)Pages: 225-225   Publisher: Institute of Advanced Engineering and Science (IAES)

Abstract

<span>In this study, the author proposed k-nearest neighbor (KNN) based heart disease prediction model. The author conducted an experiment to evaluate the performance of the proposed model. Moreover, the result of the experimental evaluation of the predictive performance of the proposed model is analyzed. To conduct the study, the author obtained heart disease data from Kaggle machine learning data repository. The dataset consists of 1025 observations of which 499 or 48.68% is heart disease negative and 526 or 51.32% is heart disease positive. Finally, the performance of KNN algorithm is analyzed on the test set. The result of performance analysis on the experimental results on the Kaggle heart disease data repository shows that the accuracy of the KNN is 91.99%</span>

Keywords:
k-nearest neighbors algorithm Computer science Data set Heart disease Span (engineering) Test data Artificial intelligence Algorithm Machine learning Internal medicine Medicine Engineering

Metrics

8
Cited By
1.38
FWCI (Field Weighted Citation Impact)
22
Refs
0.86
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Artificial Intelligence in Healthcare
Health Sciences →  Health Professions →  Health Information Management
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