ArticleEuropean heart journal. Digital health2022
Can machine learning bring cardiovascular risk assessment to the next level? A methodological study using FOURIER trial data.
Article in European heart journal. Digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The trial behind it
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Who cites it
14 citing papers in PubMed, 24 citations in OpenAlex.
- An Evaluation of Pretrained Generative Models for Augmenting Small Health Data: Comparative Modeling Study.Journal of medical Internet research · 2026Article
- Sample size calculation for training ensemble machine learning models on health data.Patterns (New York, N.Y.) · 2026Article
- Development and validation of machine learning-based risk prediction models of coronary artery disease using Porphyromonas gingivalis concentration.BMC oral health · 2026Article
- Applying Machine Learning to Predict Complex Clinical Course in Youth With Eating Disorders.The International journal of eating disorders · 2026Article
- Augmenting small tabular health data for training prognostic ensemble machine learning models using generative models.BMC medical informatics and decision making · 2025Article
- Magnitude and Impact of Hallucinations in Tabular Synthetic Health Data on Prognostic Machine Learning Models: Validation Study.Journal of medical Internet research · 2025Article
- Proteomic Signatures for Risk Prediction of Atrial Fibrillation.Circulation · 2025Article
- Improving cardiovascular risk prediction through machine learning modelling of irregularly repeated electronic health records.European heart journal. Digital health · 2024Article
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- Machine learning reveals sex-specific associations between cardiovascular risk factors and incident atherosclerotic cardiovascular disease.Scientific reports · 2023Article
- 10 Years of SYNTAX: Closing an Era of Clinical Research After Identifying New Outcome Determinants.JACC. Asia · 2023Review
- Machine Learning-Based Risk Model for Predicting Early Mortality After Surgery for Infective Endocarditis.Journal of the American Heart Association · 2022Article
- A Powerful Paradigm for Cardiovascular Risk Stratification Using Multiclass, Multi-Label, and Ensemble-Based Machine Learning Paradigms: A Narrative Review.Diagnostics (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aims: Through this proof of concept, we studied the potential added value of machine learning (ML) methods in building cardiovascular risk scores from structured data and the conditions under which they outperform linear statistical models. Methods and results: Relying on extensive cardiovascular clinical data from FOURIER, a randomized clinical trial to test for evolocumab efficacy, we compared linear models, neural networks, random forest, and gradient boosting machines for predicting the risk of major adverse cardiovascular events. To study the relative strengths of each method, we extended the comparison to restricted subsets of the full FOURIER dataset, limiting either the number of available patients or the number of their characteristics. When using all the 428 covariates available in the dataset, ML methods significantly (c-index 0.67, Conclusion: In the field of secondary cardiovascular events prevention, given the increased availability of extensive electronic health records, ML methods could open the door to more powerful tools for patient risk stratification and treatment allocation strategies.
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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.