Evidence map›Paper›PMID 38897175›Full record

ArticleCell reports. Medicine2024

Racism is an ethical issue for healthcare artificial intelligence.

Kadija Ferryman, Nina Cesare, Melissa Creary, Elaine O Nsoesie

Abstract read
In one paragraph

Article in Cell reports. Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. 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

4 authors.

Kadija FerrymanJohns Hopkins Berman Institute of Bioethics, Johns Hopkins University, Baltimore, MD, USA; Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA. Electronic address: kadija.ferryman@jhu.edu.
Nina CesareBiostatistics and Epidemiology Analytics Center, Boston University School of Public Health, Boston, MA, USA.
Melissa CrearyDepartment of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Elaine O NsoesieDepartment of Global Health, Boston University School of Public Health, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is growing attention and evidence that healthcare AI is vulnerable to racial bias. Despite the renewed attention to racism in the United States, racism is often disconnected from the literature on ethical AI. Addressing racism as an ethical issue will facilitate the development of trustworthy and responsible healthcare AI.

Indexed as

Artificial IntelligenceDelivery of Health CareRacismHumansUnited States

Identifiers

PMID38897175
PMCPMC11228769

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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 Socratic graph.