Evidence map›Paper›PMID 42536257›Full record

ReviewCurrent psychiatry reports2026

From Data to Early Diagnosis: Artificial Intelligence as a Tool to Support Screening and Detection of Autism Spectrum Disorder in Childhood.

Andrea Catalina Mahecha Ballesteros, Juanita Valeria García Bello, Eleaine Scarlet González Zuñiga, Shayra Nicole Peinado Páez, Erwin Hernando Hernández Rincón

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current psychiatry reports, 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

5 authors.

Andrea Catalina Mahecha BallesterosPrimary care physician, Universidad De La Sabana, Chía, Colombia.ORCID 0009-0006-2729-7694
Juanita Valeria García BelloPrimary care physician, Universidad De La Sabana, Chía, Colombia.ORCID 0000-0002-0959-2618
Eleaine Scarlet González ZuñigaPrimary care physician, Universidad De La Sabana, Chía, Colombia.ORCID 0009-0009-9099-3969
Shayra Nicole Peinado PáezPrimary care physician, Universidad De La Sabana, Chía, Colombia.ORCID 0009-0004-2581-5422
Erwin Hernando Hernández RincónDepartment of Family Medicine and Public Health, Universidad De La Sabana, Campus, Puente del Común, km 7 Autopista Norte, Chía, 250001, Chía, Colombia. erwinhr@unisabana.edu.co.ORCID 0000-0002-7189-5863

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewAutism spectrum disorder (ASD) is a neurodevelopmental condition with significant implications for childhood development and public health. Early detection is critical to enable timely intervention, yet access to specialised assessment remains limited in many settings. In this context, artificial intelligence (AI) has gained increasing attention as a potential tool to support early ASD screening. This review summarises recent evidence on the use of AI for the screening and early detection in childhood. RECENT

findingsRecent studies generally report favorable results for AI-based approaches, particularly in pediatric populations. Multimodal models that integrate data from questionnaires, video and audio sources tend to outperform single modality approaches, with reported improvements in accuracy and sensitivity. However, most studies remain experimental, with small sample sizes and limited validation in real world clinical environments. AI shows promise as a supportive tool for early screening, but current evidence supports its use as a complement to, rather than replacement for, clinical assessment. Further validation in routine practice is needed before widespread implementation.

Indexed as

Artificial IntelligenceAutism Spectrum DisorderEarly DiagnosisMass ScreeningChildHumansArtificial intelligenceAutism spectrum disorderEarly detectionMachine learningPediatric populationScreening

Identifiers

What OpenQuestion holds

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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.