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The most important organ for every living creature is the heart. Because the amount of heart-related deaths is rising daily, greater diligence and accuracy must be taken in the diagnosis and prognosis of heart disease. Even one mistake could have tragic results. A vital component in resolving this issue is a diseases awareness prediction system. Machine learning is one way to use artificial intelligence (AI). It is extremely beneficial for computing a range of situations related to natural catastrophes. Using standard data sets from Kaggle for training and testing, we compare the performance of machine learning techniques for heart disease prediction, such as k-proximal neighbors, Random Forest Classifier, Bagging Classifier, and Adaboost classifier. The Google Colab notebook is a great resource for Python programming because it has an enormous variety of libraries and header files that make the process easy and quick.

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Cardiovascular Disease Risk Prediction Using AI-Enabled Ensemble Bagging and Adaboost Supervised Machine-Learning Classifiers

  • 会议论文

  • 发表日期：

    2025年

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  • Yesha Patel,
  • Dushyantsinh B. Rathod,
  • Ramesh T. Prajapati,
  • Ajay Upadhyay,
  • Shri. Hardik Prajapati

摘要

The most important organ for every living creature is the heart. Because the amount of heart-related deaths is rising daily, greater diligence and accuracy must be taken in the diagnosis and prognosis of heart disease. Even one mistake could have tragic results. A vital component in resolving this issue is a diseases awareness prediction system. Machine learning is one way to use artificial intelligence (AI). It is extremely beneficial for computing a range of situations related to natural catastrophes. Using standard data sets from Kaggle for training and testing, we compare the performance of machine learning techniques for heart disease prediction, such as k-proximal neighbors, Random Forest Classifier, Bagging Classifier, and Adaboost classifier. The Google Colab notebook is a great resource for Python programming because it has an enormous variety of libraries and header files that make the process easy and quick.