Stroke Prediction Using Machine Learning Classification Methods-Reference-Cited by-同舟云学术

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Stroke Prediction Using Machine Learning Classification Methods

Published:2022-11-22 Issue: Volume: Page:
ISSN:
Container-title:2022 International Arab Conference on Information Technology (ACIT)
language:
Short-container-title:

Author:

Al-Zubaidi Hamza¹,Dweik Mohammed¹,Al-Mousa Amjed¹

Affiliation:

1. Princess Sumaya University for Technology,Computer Engineering Department,Amman,Jordan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9994070/9994081/10022050.pdf?arnumber=10022050

Reference15 articles.

1. Feature engineering made easy;ozdemir;O'Reilly Online Learning,0

2. Random oversampling and undersampling for imbalanced classification;brownlee;Machine Learning Mastery,2021

3. Opinions about oversampling in general, and the smote algorithm in particular;cummins;Cross Validated,1964

4. Smote explained for Noobs - synthetic minority over-sampling technique line by line: Rich Data;Rich Data,2021

5. Decision trees: Gini vs entropy;Quantdare,2020

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1. A heuristic‐based hybrid sampling method using a combination of SMOTE and ENN for imbalanced health data;Expert Systems;2024-03-29

2. A machine learning‐based approach for wait‐time estimation in healthcare facilities with multi‐stage queues;IET Smart Cities;2024-03-28

3. The Early Warning Signs of a Stroke: An Approach Using Machine Learning Predictions;Journal of Computer and Communications;2024

4. Harnessing the Power of Ensemble Machine Learning for the Heart Stroke Classification;EAI Endorsed Transactions on Pervasive Health and Technology;2023-12-15

5. Multiple Explainable Approaches to Predict the Risk of Stroke Using Artificial Intelligence;Information;2023-08-01

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