ArticleHealthcare (Basel, Switzerland)2025
HeartEnsembleNet: An Innovative Hybrid Ensemble Learning Approach for Cardiovascular Risk Prediction.
Article in Healthcare (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning and deep learning for diagnosis of Polyendocrine Metabolic Ovarian Syndrome: systematic review and meta-analysis.Frontiers in endocrinology · 2026Pooled it
- From Automated ECG Interpretation to Multimodal Cardiovascular Intelligence: The Evolution of Artificial Intelligence in Cardiovascular Medicine.Medical sciences (Basel, Switzerland) · 2026Review
- Early Immunological Biomarkers for Personalized Treatment Selection in Severe COVID-19: Post Hoc Machine Learning Analysis of a Randomized Clinical Trial.JMIR medical informatics · 2026Article
- Evaluating Biomedical Feature Fusion on Machine Learning's Predictability and Interpretability of COVID-19 Severity Types: Model Development, Interpretation, and Validation.JMIR formative research · 2026Article
- Individualized Risk Stratification for Early Recurrence of Hepatocellular Carcinoma: A Clinical Tool Derived from a Large-Scale (n=3084) Cohort Study.Journal of hepatocellular carcinoma · 2026Article
- Digital Health Delivery Models for Hypertension Self-Care in Asia: A Systematic Review.Journal of multidisciplinary healthcare · 2026Review
- Increasing burden of lower extremity peripheral arterial disease in Sub-Saharan Africa, 1990-2021 - results from the global burden of disease study 2021.American heart journal plus : cardiology research and practice · 2026Article
- SR-HCC Score: A Novel Nomogram for Predicting Spontaneous Rupture in Hepatocellular Carcinoma Patients.Journal of hepatocellular carcinoma · 2026Article
- Influence of Continuous Predictor Modelling Methods on Prediction Stability in Clinical Prediction Model Development: An Empirical Comparison Using Real Clinical Data.Clinical epidemiology · 2026Article
- Integrative Machine Learning and Experimental Validation Identify MYBL2 as a Prognostic Biomarker and Therapeutic Target in Hepatocellular Carcinoma.Oncology research · 2026Article
- The Impact of Fluid Balance on Clinical Outcomes in ICU Patients with Pulmonary Arterial Hypertension: A Retrospective Analysis using MIMIC-IV.The open respiratory medicine journal · 2026Article
- Automated assessment of breast arterial calcification: a new frontier in cardiovascular risk prediction.Frontiers in cardiovascular medicine · 2026Review
- Biodata-centric cardiovascular disease prediction using multi-objective genetic algorithm-driven deep ensembles.Scientific reports · 2025Article
- Cardiovascular risk prediction via ensemble machine learning and oversampling methods.Scientific reports · 2025Article
- Integrating artificial intelligence in healthcare: applications, challenges, and future directions.Future science OA · 2025Review
- Comparison of the predictive performance of Cumulative Illness Rating Scale, Charlson Comorbidity Index and COMCOLD Index for moderate-to-severe exacerbations in elderly subjects with chronic obstructive pulmonary disease.Annals of medicine · 2025Observational
- A machine-learning-derived online screening tool for depressive symptoms in patients with cardiovascular and cerebrovascular diseases (CCVD): a cross-sectional study with temporal validation from CHARLS.BMC cardiovascular disorders · 2025Article
- AHE-FNUQ: An Advanced Hierarchical Ensemble Framework with Neural Network Fusion and Uncertainty Quantification for Outlier Detection in Agri-IoT.Sensors (Basel, Switzerland) · 2025Article
- Interleukin-6, serum albumin levels, and acute kidney injury jointly predict in-hospital mortality in pediatric COVID-19 patients.Translational pediatrics · 2025Article
- Multimodal large language models in ultrasound diagnosis of breast masses: a multicenter comparative analysis based on GPT-4o, radiologists, and convolutional neural network (CNN).Quantitative imaging in medicine and surgery · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCardiovascular disease (CVD) is a prominent determinant of mortality, accounting for 17 million lives lost across the globe each year. This underscores its severity as a critical health issue. Extensive research has been undertaken to refine the forecasting of CVD in patients using various supervised, unsupervised, and deep learning approaches.
methodsThis study presents HeartEnsembleNet, a novel hybrid ensemble learning model that integrates multiple machine learning (ML) classifiers for CVD risk assessment. The model is evaluated against six classical ML classifiers, including support vector machine (SVM), gradient boosting (GB), decision tree (DT), logistic regression (LR), k-nearest neighbor (KNN), and random forest (RF). Additionally, we compare HeartEnsembleNet with Hybrid Random Forest Linear Models (HRFLM) and ensemble techniques including stacking and voting.
resultsEmploying a dataset of 70,000 cardiac patients with 12 clinical attributes, our proposed model achieves a notable accuracy of 92.95% and a precision of 93.08%.
conclusionsThese results highlight the effectiveness of hybrid ensemble learning in enhancing CVD risk prediction, offering a promising framework for clinical decision support.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.