Article

An Improved Decision Tree Model with Hybrid Training Subset Selection for Robust Cardiovascular Disease Prediction

2026-05-19

Abstract excerpt

<title>Abstract</title> <p>Cardiovascular diseases (CVDs) are the number one cause of death globally, and the development of reliable, accurate, and robust predictive models for early detection and diagnosis of CVDs is highly needed. Conventional machine learning models typically use a single random data split, which can introduce bias, hinder generalization, and have a limited clinical impact. To overcome these...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 8c8bf702-1226-5938-b770-a58484a6f6db
DOI: 10.21203/rs.3.rs-9742959/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

An Improved Decision Tree Model with Hybrid Training Subset Selection for Robust Cardiovascular Disease PredictionDOI 10.21203/rs.3.rs-9742959/v1Read

Enhanced machine learning and hybrid ensemble approaches for coronary heart disease predictionSemantic proximity Read

Feature optimized hybrid model for prediction of myocardial infarctionSemantic proximity Read

Discovering biomarkers associated and predicting cardiovascular disease with high accuracy using a novel nexus of machine learning techniques for precision medicineSemantic proximity Read

A Hybrid Approach for Cardiovascular Disease Diagnosis: J48 ClassifierSemantic proximity Read

An Efficient Hybrid Classification Model for Heart Disease PredictionSemantic proximity Read

Comparison of Assembly Methods in Machine Learning for the Early Prediction of Acute Myocardial InfarctionSemantic proximity Read

Predicting Cardiovascular Disease with Machine Learning: A Comparative Analysis of Classification ModelsSemantic proximity Read

Advancements in Cardiovascular Disease Detection: Leveraging Data Mining and Machine LearningSemantic proximity Read

Integrating Healthcare Analytics to Improve Diabetes Management and Prevent Heart Attacks: A Data-Driven ApproachSemantic proximity Read

Evaluating Feature Selection Methods and Feature Contributions for Cardiovascular Disease Risk PredictionSemantic proximity Read

Enhancing Prediction of Heart Disease Using Hybrid Machine Learning Methods XGBoost and K-Means ClusteringSemantic proximity Read

Development of a Machine-learning Based Diagnosis Procedure to Distinguish Aortic Dissection from Non-ST- Elevation Myocardial InfarctionSemantic proximity Read