Stroke Prediction Model Based on Decision Tree

Yuheng Liu; Chenxuan Zhang; Xiaoyang Zheng; Yuhan Liu; Jiangping He

doi:10.37394/23208.2023.20.3

March 7, 2023WSEAS TRANSACTIONS ON BIOLOGY AND BIOMEDICINEOpen Access

Stroke Prediction Model Based on Decision Tree

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Key Points

To develop and evaluate a decision tree-based machine learning model for predicting stroke risk and compare its performance against a Naive Bayes classifier.
Preprocessed a stroke dataset in Python and computed Gini coefficients across features to determine optimal tree splits.
Trained and evaluated both a decision tree model and a Naive Bayes classifier to predict stroke likelihood on test samples.
The decision tree model achieved a prediction accuracy of 88%, compared to 79% for the Naive Bayes model.
Advanced age, high blood pressure, heart disease, and habitual smoking were identified as key risk factors contributing to increased stroke probability.

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Implication

Shows superior stroke prediction accuracy for decision tree models over Naive Bayes in high-risk individuals, highlighting the impact of cardiovascular risk factors.

Abstract

In this paper, the predictive model of stroke based on decision tree is implemented to predict the stroke probability of ten samples by using Python language. The dataset of stroke is collected and is preprocessed, then the Gini coefficients of each feature are calculated to select the division, and then the decision tree model is obtained. Finally, the stroke probability is predicted for ten samples. In addition, Naive Bayes model is applied to predict the stroke probability to compare with the decision tree method. The experimental results show that older people with high blood pressure, heart disease, habitual smoking are more possible to have stroke, with a prediction accuracy of 88% for decision tree method and 79% for Naive Bayes model, respectively.

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Cite This Study

Liu et al. (2023) studied this question.

synapsesocial.com/papers/6aa17107b6711a872fed6f94 https://doi.org/10.37394/23208.2023.20.3

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Stroke Prediction Model Based on Decision Tree

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Stroke Prediction Model Based on Decision Tree

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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