ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2022
Assessing Phenotype Definitions for Algorithmic Fairness.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed.
- Linking "Big" Geospatial and Health Data: Implications for Research in Environmental Epidemiology.Environmental health perspectives · 2026Article
- Improving classification of myocardial infarction with machine learning in a diverse population.American journal of epidemiology · 2026Article
- Multi-domain rule-based phenotyping algorithms enable improved GWAS signal.NPJ digital medicine · 2025Article
- Developing and sustaining inclusive language in biomedical informatics communications: an AMIA Board of Directors endorsed paper on the Inclusive Language and Context Style Guidelines.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- A Generalized Tool to Assess Algorithmic Fairness in Disease Phenotype Definitions.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2025Article
- Contextualized race and ethnicity annotations for clinical text from MIMIC-III.Scientific data · 2024Article
- Electronic Health Record Phenotyping of Pediatric Suicide-Related Emergency Department Visits.JAMA network open · 2024Article
- Causal fairness assessment of treatment allocation with electronic health records.Journal of biomedical informatics · 2024Article
- Improving reporting standards for phenotyping algorithm in biomedical research: 5 fundamental dimensions.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Cross Biobank Comparison of Phenomic Profiles.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phenotyping is a core, routine activity in observational health research. Cohorts impact downstream analyses, such as how a condition is characterized, how patient risk is defined, and what treatments are studied. It is thus critical to ensure that cohorts are representative of all patients, independently of their demographics or social determinants of health. In this paper, we propose a set of best practices to assess the fairness of phenotype definitions. We leverage established fairness metrics commonly used in predictive models and relate them to commonly used epidemiological metrics. We describe an empirical study for Crohn's disease and diabetes type 2, each with multiple phenotype definitions taken from the literature across gender and race. We show that the different phenotype definitions exhibit widely varying and disparate performance according to the different fairness metrics and subgroups. We hope that the proposed best practices can help in constructing fair and inclusive phenotype definitions.
Indexed as
Identifiers
37128361PMC10148336What Socratic holds
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.