ArticleScience advances2023
Use of race in clinical algorithms.
Article in Science advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
What it found
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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
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Artificial Intelligence Models for Time-to-Event Outcome Applied in Cardiovascular Disease Risk Prediction.Journal of medical systems · 2024Pooled it
- Racialized Heteroscedasticity in Neuroimaging Features, Behavior Measures, and Neuroimaging-Based Predictive Models.Research square · 2026Article
- A pipeline for enabling path-specific causal fairness in observational health data.Proceedings of the ... Conference on Fairness, Accountability, and Transparency · 2026Article
- Reconsidering the use of race, sex, and age in clinical algorithms to address bias in practice: A discussion paper.International journal of nursing studies advances · 2025Review
- What Is Fair? Defining Fairness in Machine Learning for Health.Statistics in medicine · 2025Review
- Role and Use of Race in Artificial Intelligence and Machine Learning Models Related to Health.Journal of medical Internet research · 2025Article
- Raising awareness of potential biases in medical machine learning: Experience from a Datathon.PLOS digital health · 2025Article
- Predictive Factors of Apparent Treatment Resistant Hypertension Among Patients With Hypertension Identified Using Electronic Health Records.Journal of general internal medicine · 2025Article
- Online database of clinical algorithms with race and ethnicity.Scientific reports · 2025Article
- Demographic bias of expert-level vision-language foundation models in medical imaging.Science advances · 2025Article
- Article
- Online Database of Clinical Algorithms with Race and Ethnicity.medRxiv : the preprint server for health sciences · 2025Article
- Value of diversity characteristics in predictive modeling: ACS screening as a case study.NPJ cardiovascular health · 2025Article
- Geneticization in the genomic era: a scoping review of ethical, clinical, and sociocultural transformations.Frontiers in sociology · 2025Review
- TEX10: A Novel Drug Target and Potential Therapeutic Direction for Sleep Apnea Syndrome.Nature and science of sleep · 2025Article
- Governance for anti-racist AI in healthcare: integrating racism-related stress in psychiatric algorithms for Black Americans.Frontiers in digital health · 2025Article
- Machine learning-based prediction models in medical decision-making in kidney disease: patient, caregiver, and clinician perspectives on trust and appropriate use.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Guidance for unbiased predictive information for healthcare decision-making and equity (GUIDE): considerations when race may be a prognostic factor.NPJ digital medicine · 2024Article
- The limits of fair medical imaging AI in real-world generalization.Nature medicine · 2024Article
- Understanding AI bias in clinical practice.Heart rhythm · 2024Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To answer whether patients' race belongs in clinical prediction algorithms, two types of prediction models are considered: (i) diagnostic, which describes a patient's clinical characteristics, and (ii) prognostic, which forecasts a clinical risk or treatment effect that a patient is likely to experience in the future. The ex ante equality of opportunity framework is used, where specific health outcomes, which are prediction targets, evolve dynamically due to the effects of legacy levels of outcomes, circumstances, and current individual efforts. In practical settings, this study shows that failure to include race corrections will propagate systemic inequities and discrimination in any diagnostic model and specific prognostic models that inform decisions by invoking an ex ante compensation principle. In contrast, including race in prognostic models that inform resource allocations following an ex ante reward principle can compromise the equality of opportunities for patients from different races. Simulation results demonstrate these arguments.
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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.