Mar 1, 2022 · ... Research Paper. Transfer learning-based machine learning models for heart disease prediction in an earlier stage. Authors: Ganaga Muneeswari M ...
Available online at: https://www.ijariit.com. Transfer learning-based machine learning models for heart disease prediction in an earlier stage. Ganaga ...
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Mar 12, 2024 · This research aims to develop a robust survival prediction model for heart failure patients using advanced machine learning techniques.
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People also ask
Which machine learning algorithm is best for heart disease prediction?
A 10-fold cross-validation approach was employed during the model development process. The results indicated that the decision tree algorithm achieved the highest accuracy in predicting heart disease, with a rate of 93.19%, followed by the SVM algorithm at 92.30%.
What model is used to predict heart disease?
The Heart Disease Prediction System incorporates the Naive Bayesian Classification technique to assist in making decisions. By analyzing a vast database of past heart disease cases, the system uncovers valuable insights. This model is highly efficient in identifying patients at risk of heart disease.
What are machine learning predictive models for detection of cardiovascular diseases?
Then, we investigated and applied seven machine learning-driven predictive models that can enhance the detection of cardiovascular and cerebrovascular diseases; these models include K-Nearest Neighbors, Support Vector Machine, Logistic Regression, Convolutional Neural Network, Gradient Boost, XGBoost, and Random Forest ...
What algorithms are used to predict heart attacks?
Several studies have utilized ML algorithms like SVM, artificial neural networks (ANN), DT, LR, and RF to analyze medical data and predict heart diseases. A recent study by6used ML models to predict the risk of cardiac disease in a multi-ethnic population.
Sep 4, 2024 · This study is aimed at building a potential machine learning model to predict heart disease in early stage employing several feature selection techniques.
Authors have used most of the machine learning and deep learning ensemble algorithms so that they can predict heart disease at the early stage.
This research focuses on supervised machine learning techniques as a potential tool for heart disease prediction.
This study proposes an AI‐enabled stroke prediction architecture consisting of FL based on the artificial neural network (ANN) model using data from actual ...
... heart disease prediction systems. Various techniques and data mining classifiers are defined in this work for efficient and effective heart disease prediction.
This research aims to construct a machine learning-based ... Disease Prediction System Using Machine Learning. ... The paper explores machine learning algorithms ...
Aug 4, 2023 · We developed machine learning models for predicting CHD. The TyG-index was substituted for diabetes in CHD prediction models.