ReviewThe Brown journal of hospital medicine2023
Misguided Artificial Intelligence: How Racial Bias is Built Into Clinical Models.
Review in The Brown journal of hospital medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Assessing the effect of race on machine learning models predicting hospital admissions from emergency department.JAMIA open · 2026Article
- The spatial revolution in immuno-oncology: artificial intelligence decoding NK cell niches to predict therapeutic response.Frontiers in immunology · 2026Review
- Fair positive unlabeled learning for predicting undiagnosed Alzheimer's disease in diverse electronic health records.NPJ digital medicine · 2025Article
- Role and Use of Race in Artificial Intelligence and Machine Learning Models Related to Health.Journal of medical Internet research · 2025Article
- Ethical data acquisition for LLMs and AI algorithms in healthcare.NPJ digital medicine · 2024Review
- Coding Fairness: Detecting Demographic-Related Coding Discrepancies in ICD Code Assignments.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
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence is being used today to solve a myriad of problems. While there is significant promise that AI can help us address many healthcare issues, there is also concern that health inequities can be exacerbated. This article looks specifically at predictive models in regards to racial bias. Each phase of the model building process including raw data collection and processing, data labelling, and implementation of the model can be subject to racial bias. This article aims to explore some of the ways in which this occurs.
Indexed as
Identifiers
What 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.