ArticleOpen medicine (Warsaw, Poland)2022
Risk prediction of cardiovascular disease using machine learning classifiers.
Article in Open medicine (Warsaw, Poland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it, 145 citations in OpenAlex.
- Prognostic models in populations with heart failure: a systematic review and meta-analysis.Systematic reviews · 2026Pooled it
- Evaluating predictive performance, validity, and applicability of machine learning models for predicting HIV treatment interruption: a systematic review.BMC global and public health · 2025Pooled it
- Clinical and Behavioral Determinants of Type 2 Diabetes Remission After Bariatric Surgery: An Explainable Machine Learning Approach.Journal of clinical medicine · 2026Article
- A risk prediction model for gastrointestinal bleeding in coronary heart disease patients undergoing dual antiplatelet therapy after percutaneous coronary intervention.Pakistan journal of medical sciences · 2025Article
- Implementation of a Deep Learning System for Detection and Classification of Lumpy Skin Disease in Cattle: Enhancing Precision and Efficiency in Veterinary Diagnostics.Veterinary medicine and science · 2025Article
- Predicting cardiovascular risk with hybrid ensemble learning and explainable AI.Scientific reports · 2025Article
- Retinal Microvascular Characteristics-Novel Risk Stratification in Cardiovascular Diseases.Diagnostics (Basel, Switzerland) · 2025Article
- Explainable machine learning for predicting lung metastasis of colorectal cancer.Scientific reports · 2025Article
- Article
- Enhanced cardiovascular risk prediction in the Western Pacific: A machine learning approach tailored to the Malaysian population.PloS one · 2025Article
- A comparative analysis of the binary and multiclass classified chest X-ray images of pneumonia and COVID-19 with ML and DL models.Open medicine (Warsaw, Poland) · 2025Article
- Interpretable AI-driven multi-objective risk prediction in heart failure patients with thyroid dysfunction.Frontiers in digital health · 2025Article
- The Co-Piloting Model for Using Artificial Intelligence Systems in Medicine: Implementing the Constrained-Disorder-Principle-Based Second-Generation System.Bioengineering (Basel, Switzerland) · 2024Review
- Detection of cardiovascular disease cases using advanced tree-based machine learning algorithms.Scientific reports · 2024Article
- Advanced statistical methods for hazard modeling in cardiothoracic surgery: a comprehensive review of techniques and approaches.Indian journal of thoracic and cardiovascular surgery · 2024Article
- CardioRiskNet: A Hybrid AI-Based Model for Explainable Risk Prediction and Prognosis in Cardiovascular Disease.Bioengineering (Basel, Switzerland) · 2024Article
- Machine learning approach for predicting cardiovascular disease in Bangladesh: evidence from a cross-sectional study in 2023.BMC cardiovascular disorders · 2024Article
- Development and validation of a cardiovascular risk prediction model for Sri Lankans using machine learning.PloS one · 2024Article
- Social Determinants of Health Data Improve the Prediction of Cardiac Outcomes in Females with Breast Cancer.Cancers · 2023Article
- A Disentangled VAE-BiLSTM Model for Heart Rate Anomaly Detection.Bioengineering (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiovascular disease (CVD) makes our heart and blood vessels dysfunctional and often leads to death or physical paralysis. Therefore, early and automatic detection of CVD can save many human lives. Multiple investigations have been carried out to achieve this objective, but there is still room for improvement in performance and reliability. This study is yet another step in this direction. In this study, two reliable machine learning techniques, multi-layer perceptron (MLP), and
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Registered trials
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 Socratic graph.