Evidence mapPaperPMID 42499775Full record

ReviewPediatric investigation2026

Artificial intelligence, equity, and pediatric neurodevelopmental disorders: A scoping review of clinical practice applications.

Florida Uzoaru, Obinna O Oleribe, Ucheoma Nwaozuru, Parichart Sabado

Abstract readReview
In one paragraph

Review in Pediatric investigation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Florida UzoaruCollege of Nursing and Health Sciences Southeastern Louisiana University Hammond Louisiana USA.
Obinna O OleribeDepartment of Health Sciences School of Public Health and Health Sciences California State University Dominguez Hills Carson California USA.
Ucheoma NwaozuruWake Forest School of Medicine Division of Public Health Science Raleigh North Carolina USA.
Parichart SabadoDepartment of Health Sciences School of Public Health and Health Sciences California State University Dominguez Hills Carson California USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is increasingly being used in healthcare and has the potential to improve the diagnosis, treatment, monitoring, and management of neurodevelopmental disorders (NDDs) in children. Early identification and personalized care are often constrained by subjective assessment and inequitable access. AI tools may enhance diagnostic accuracy and care delivery; however, the maturity, clinical readiness, and equity implications of this evidence base remain unclear. This scoping review mapped peer-reviewed studies published in English since 2015 that described empirical or conceptual AI applications for diagnosis, monitoring, decision support, or treatment in pediatric NDD care, with particular attention to equity considerations. From 1027 records, 13 studies met the inclusion criteria. Most focused on attention deficit/hyperactivity disorder (ADHD,

Indexed as

Artificial intelligenceClinical practiceHealth equityNeurodevelopmental disorders

Identifiers

PMID42499775
PMCPMC13399598

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.