Coronary heart disease prediction method fusing domain|adaptive ...

Coronary heart disease prediction method fusing domain-adaptive ...

Graph convolutional networks (GCNs) have achieved impressive results in many medical scenarios involving graph node classification tasks.

Domain-adaptive-Transfer-Learning-with-Graph-Convolutional ...

This repository contains the author's implementation in PyTorch for the paper "Coronary Heart Disease Prediction Method Fusing Domain-adaptive Transfer Learning

Predicting Coronary Heart Disease Using a Suite of Machine ... - arXiv

This literature review examines machine learning techniques for CHD prediction, focusing on methodologies, results, and limitations of existing research.

Predicting early-stage coronary artery disease using machine ...

Based on the features' importance in several algorithms and our experts' clinical expertise, we selected the most important ones. This approach ...

Enhanced feature selection and ensemble learning for ... - Frontiers

Results: On the results, our heart disease prediction model yielded an accuracy of 83.0%, and a balanced F1 score of 84.0%. The integration of ...

A Study on Coronary Disease Prediction Using Boosting-based ...

In this paper, we attempt to focus on coronary heart disease prediction. ... Several boosting algorithms of ensemble techniques like Adaptive Boosting ...

Prediction of Coronary Heart Disease using Machine Learning

Using the South African Heart Disease dataset of 462 instances, intelligent models are derived by the considered ML techniques using 10-fold cross validation.

Machine Learning-Based Predictive Models for Detection of ...

... algorithm in this specific domain. Figure 5 ... Prediction of Coronary Artery Disease Using Machine Learning Techniques with Iris Analysis.

Early detection of coronary heart disease using ensemble techniques

Artificial Neural Networks have been employed in previous research related to heart disease prediction. Olaniyi and Oyedotun [17] proposed a three-step model ...

(PDF) Predicting Coronary Heart Disease Using a Suite of Machine ...

This liter- ature review examines machine learning techniques for CHD prediction, focusing on methodologies, results, and limitations of existing research.

A proposed technique for predicting heart disease using machine ...

Similarly, another study byapplied a deep learning (DL) algorithm to predict coronary artery disease (CAD). The researchers utilized clinical ...

Coronary Artery Disease prediction using Machine Learning ...

The proposed system detects coronary heart disease based on boosting methods, a machine learning methodology.

Deep Featured Adaptive Dense Net Convolutional Neural Network ...

To resolve this problem, we propose an Enhanced Healthcare data analysis model for cardiac data prediction using an adaptive Deep Featured Adaptive Convolution ...

A novel attention-based cross-modal transfer learning framework for ...

The realm of predicting Cardiovascular disease (CVD) using machine learning and deep learning techniques has witnessed substantial advancements in recent years.

Prediction of Coronary Heart Disease using Supervised Machine ...

This work aims to predict the risk of CHD using machine learning algorithms like Random Forest, Decision Trees, and K-Nearest Neighbours using “Framingham ...

Modified Self-Adaptive Bayesian Algorithm for Smart Heart Disease ...

Predictions can be made using machine learning algorithms, and the accuracy of those predictions is assessed by contrasting different techniques ...

A hybrid machine learning approach integrating oversampling and ...

This study presents a novel approach to enhance cardiovascular disease prediction using a hybrid machine learning (ML) model.

Adaptive mining prediction model for content recommendation to ...

This paper proposes the Fuzzy Rule-based Adaptive Coronary Heart Disease Prediction Support Model (FbACHD_PSM), which gives content recommendation to ...

Prediction of Heart Disease using an Ensemble Learning Approach

We used the proposed model with three datasets: the StatLog UCI dataset, the Z-Alizadeh Sani dataset, and the Cardiovascular Disease (CVD) dataset. We obtained ...

New cardiovascular disease prediction approach using support ...

[4] proposed the GWO-SVM classification model for predicting heart disease. The proposed method is a combination of the feature selection method ...