ArticleOpen heart2023
Algorithmic fairness in cardiovascular disease risk prediction: overcoming inequalities.
Article in Open heart, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Development and evaluation of cardiovascular disease risk prediction models for patients with type 2 diabetes.Scientific reports · 2026Article
- Navigating fairness aspects of clinical prediction models.BMC medicine · 2025Article
- What Is Fair? Defining Fairness in Machine Learning for Health.Statistics in medicine · 2025Review
- Bottlenecks in advancing and applying multiomic data integration-common data resources as rate-limiting drivers-the high-impact use case of atherosclerotic cardiovascular disease.Briefings in bioinformatics · 2025Review
- Ensemble learning approach with explainable AI for improved heart disease prediction.Frontiers in pharmacology · 2025Article
- Mitigating Algorithmic Bias in AI-Driven Cardiovascular Imaging for Fairer Diagnostics.Diagnostics (Basel, Switzerland) · 2024Article
- Artificial intelligence bias in the prediction and detection of cardiovascular disease.NPJ cardiovascular health · 2024Review
Corrections and comments
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Authors and funding
1 author.
Funding
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Abstract
The main purpose of prognostic risk prediction models is to identify individuals who are at risk of disease, to enable early intervention. Current prognostic cardiovascular risk prediction models, such as the Systematic COronary Risk Evaluation (SCORE2) and the SCORE2-Older Persons (SCORE2-OP) models, which represent the clinically used gold standard in assessing patient risk for major cardiovascular events in the European Union (EU), generally overlook socioeconomic determinants, leading to disparities in risk prediction and resource allocation. A central recommendation of this article is the explicit inclusion of individual-level socioeconomic determinants of cardiovascular disease in risk prediction models. The question of whether prognostic risk prediction models can promote health equity remains to be answered through experimental research, potential clinical implementation and public health analysis. This paper introduces four distinct fairness concepts in cardiovascular disease prediction and their potential to narrow existing disparities in cardiometabolic health.
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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 OpenQuestion graph.