Evidence map›Paper›PMID 37036866›Full record

ArticlePLOS digital health2023

Equity should be fundamental to the emergence of innovation.

Jack Gallifant, Luis Filipe Nakayama, Judy Wawira Gichoya, Robin Pierce, Leo Anthony Celi

Abstract read
In one paragraph

Article in PLOS digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Equity by design principles for digital health interventions.International journal for equity in health · 2025
    Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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

5 authors.

Jack GallifantDepartment of Critical Care, Guy's and St Thomas' NHS Trust, London, United Kingdom.ORCID https://orcid.org/0000-0003-1306-2334
Luis Filipe NakayamaLaboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
Judy Wawira GichoyaEmory University School of Medicine, Department of Radiology, Atlanta, Georgia, United States of America.
Robin PierceThe Law School, Faculty of Humanities, Arts, and Social Sciences, University of Exeter, Exeter EX4 4HY, United Kingdom.
Leo Anthony CeliLaboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability of artificial intelligence to perpetuate bias at scale is increasingly recognized. Recently, proposals for implementing regulation that safeguards such discrimination have come under pressure due to the potential of such restrictions stifling innovation within the field. In this formal comment, we highlight the potential dangers of such views and explore key examples that define this relationship between health equity and innovation. We propose that health equity is a vital component of healthcare and should not be compromised to expedite the advancement of results for the few at the expense of vulnerable populations. A data-centered future that works for all will require funding bodies to incentivize equity-focused AI, and organizations must be held accountable for the differential impact of such algorithms post-deployment.

Identifiers

PMID37036866
PMCPMC10085007

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.