Evidence map›Paper›PMID 40994240›Full record

ArticleClinical and translational science2025

Racing Against the Algorithm: Leveraging Inclusive AI as an Antiracist Tool for Brain Health.

Victor Ekuta

Abstract read
In one paragraph

Article in Clinical and translational science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Victor EkutaNeurology Resident Physician, Morehouse School of Medicine, Atlanta, Georgia, USA.ORCID 0000-0002-2191-3437

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is transforming medicine, including neurology and mental health. Yet without equity-centered design, AI risks reinforcing systemic racism. This article explores how algorithmic bias and phenotypic exclusion disproportionately affect marginalized communities in brain health. Drawing on lived experience and scientific evidence, the essay outlines five design principles-centered on inclusion, transparency, and accountability-to ensure AI promotes equity. By reimagining AI as a tool for justice, we can reshape translational science to serve all populations.

Indexed as

AlgorithmsArtificial IntelligenceSystemic RacismBrainHealth EquityHumansMental Healthartificial intelligencebrain healthclinical algorithmshealth equityinclusive designmachine learningracial disparitiestranslational science

Identifiers

PMID40994240
PMCPMC12461116

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

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.