Application and comparison of decision tree algorithm and K-Nearest Neighbors algorithm in heart disease prediction

Research Article
Open access

Application and comparison of decision tree algorithm and K-Nearest Neighbors algorithm in heart disease prediction

Yiran Wang 1*
  • 1 School of Management, Hefei University of Technology, Hefei, Anhui, 230000, China    
  • *corresponding author 2020211627@mail.hfut.edu.cn
Published on 31 January 2024 | https://doi.org/10.54254/2755-2721/30/20230082
ACE Vol.30
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-83558-285-5
ISBN (Online): 978-1-83558-286-2

Abstract

In the past two decades, rapid industrialization and urbanization have led to tremendous economic growth and an improvement in people's living standards. However, the impact of people's irregular lifestyles and habits on their health has gradually emerged. Among them, cardiovascular diseases have become particularly prominent, with increasing incidence and mortality rates, especially in developing countries. Heart disease is a major cause of the rising death rates. Early-stage prediction of heart disease poses a major challenge in clinical analysis. Today, the adoption of appropriate decision support systems to achieve cost reduction in clinical trials has become a future development trend for many hospitals. This study compares decision tree classification and K-nearest neighbors (KNN) classification algorithms to seek better diagnostic performance for heart disease. The existing dataset of heart disease patients from the Cleveland database is used to te3st and demonstrate the performance of all algorithms, providing support for the establishment of a heart disease prediction system. This, in turn, can assist doctors in making more accurate diagnoses and timely interventions before the onset of heart disease, thereby reducing the mortality rate of heart disease from the source.

Keywords:

Machine Learning, Heart Disease, Classification, Prediction, Decision Tree, K-Nearest Neighbors

Wang,Y. (2024). Application and comparison of decision tree algorithm and K-Nearest Neighbors algorithm in heart disease prediction. Applied and Computational Engineering,30,111-117.
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References

[1]. Qin C C 2022 Research on heart disease prediction based on catboost model Qufu Normal University p 53 doi:10.27267/d.cnki.gqfsu.2022.001453.

[2]. Wang X 2022 Study on machine learning based heart disease prediction model Xinan Daxue p 57 doi:10.27684/d.cnki.gxndx.2022.001659.

[3]. Xin R H, Dong Z Y, Miao F B, Wang T T, Li Y R and Feng X 2022 Research on heart disease prediction model based on machine learning Jilin Huagong Xueyuan Xuebao 39(09) p 27-32 doi:10.16039/j.cnki.cn22-1249.2022.09.006.

[4]. Zheng L J and Song B 2023 Pre- Pruning and Optimization of Decision Tree Classification Algorithm Zidonghua Yibiao 44(05) p 56-62 doi: 10.16086/j.cnki.issn1000-0380.2023020066.

[5]. Kotsiantis S B 2013 Decision trees:a recent overview Artificial Intelligence Review 39(4) p 261-283 doi:10.1007/s10462-011-9272-4.

[6]. Zhao X M, Wei X J, Wang N and Lei X J 2020 Feature Aggregation Decision Tree Prediction Model for Rainfall Landslide Disaster J. Catastrophology 35(01) p 27-31

[7]. Baidya A, Pasha A, Pavani B R, Paul A and Wali A 2020 Comparative Analysis of Multiple classifiers for Heart Disease Classification International J. Advanced Research Comp. Sci. 11(3) p 6-11 doi:10.26483/ijarcs.v11i3.6523.

[8]. Liang J H and Xu Y J 2022 Research on Predictive Diagnosis Model of Heart Disease Based on Machine Learning Algorithm Modern Inf. Tech. 6(19) p 67-70 doi: 10.19850/j.cnki.2096-4706.2022.19.017.

[9]. Tang Y F, Ke Y B, Zhuang L Y, Ji R D, Chen J Z and Yu K H 2023 Pipelines Ultrasonic Guided Wave Classification Based on Confusion Matrix Neural Network Chinese J. Election Devices 46(02) p 469-477

[10]. Chicco D and Jurman G 2020 The advantages of the Matthews correlation coefficient (MCC)over F1 score and accuracy in binary classification evaluation BMC Genomics 21(6) p 4-5 doi:10.1186/s12864-019-6413-7.

[11]. Xing W C and Bei Y L 2020 Medical Health Big Data Classification Based on KNN Classification Algorithm IEEE Access 8(86) p 28808-28819 doi: 10.1109/access.2019.2955754.

Cite this article

Wang,Y. (2024). Application and comparison of decision tree algorithm and K-Nearest Neighbors algorithm in heart disease prediction. Applied and Computational Engineering,30,111-117.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2023 International Conference on Machine Learning and Automation

ISBN：978-1-83558-285-5(Print) / 978-1-83558-286-2(Online)
Editor：Mustafa İSTANBULLU
Conference website: https://2023.confmla.org/
Conference date: 18 October 2023
Series: Applied and Computational Engineering
Volume number: Vol.30
ISSN：2755-2721(Print) / 2755-273X(Online)

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References

[1]. Qin C C 2022 Research on heart disease prediction based on catboost model Qufu Normal University p 53 doi:10.27267/d.cnki.gqfsu.2022.001453.

[2]. Wang X 2022 Study on machine learning based heart disease prediction model Xinan Daxue p 57 doi:10.27684/d.cnki.gxndx.2022.001659.

[3]. Xin R H, Dong Z Y, Miao F B, Wang T T, Li Y R and Feng X 2022 Research on heart disease prediction model based on machine learning Jilin Huagong Xueyuan Xuebao 39(09) p 27-32 doi:10.16039/j.cnki.cn22-1249.2022.09.006.

[4]. Zheng L J and Song B 2023 Pre- Pruning and Optimization of Decision Tree Classification Algorithm Zidonghua Yibiao 44(05) p 56-62 doi: 10.16086/j.cnki.issn1000-0380.2023020066.

[5]. Kotsiantis S B 2013 Decision trees:a recent overview Artificial Intelligence Review 39(4) p 261-283 doi:10.1007/s10462-011-9272-4.

[6]. Zhao X M, Wei X J, Wang N and Lei X J 2020 Feature Aggregation Decision Tree Prediction Model for Rainfall Landslide Disaster J. Catastrophology 35(01) p 27-31

[7]. Baidya A, Pasha A, Pavani B R, Paul A and Wali A 2020 Comparative Analysis of Multiple classifiers for Heart Disease Classification International J. Advanced Research Comp. Sci. 11(3) p 6-11 doi:10.26483/ijarcs.v11i3.6523.

[8]. Liang J H and Xu Y J 2022 Research on Predictive Diagnosis Model of Heart Disease Based on Machine Learning Algorithm Modern Inf. Tech. 6(19) p 67-70 doi: 10.19850/j.cnki.2096-4706.2022.19.017.

[9]. Tang Y F, Ke Y B, Zhuang L Y, Ji R D, Chen J Z and Yu K H 2023 Pipelines Ultrasonic Guided Wave Classification Based on Confusion Matrix Neural Network Chinese J. Election Devices 46(02) p 469-477

[10]. Chicco D and Jurman G 2020 The advantages of the Matthews correlation coefficient (MCC)over F1 score and accuracy in binary classification evaluation BMC Genomics 21(6) p 4-5 doi:10.1186/s12864-019-6413-7.

[11]. Xing W C and Bei Y L 2020 Medical Health Big Data Classification Based on KNN Classification Algorithm IEEE Access 8(86) p 28808-28819 doi: 10.1109/access.2019.2955754.

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