Evidence map›Paper›PMID 42746007›Full record

ArticleFrontiers in neuroinformatics2026

Toward FIAP

Yves Fuamba

Abstract read
In one paragraph

Article in Frontiers in neuroinformatics, 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

1 author.

Yves FuambaDepartment of Autism Research, Antibiostress Clinics, Gloucester, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autism spectrum disorder is characterized by substantial heterogeneity across biological burden, adaptive reserve, developmental timing, therapeutic engagement, and intervention responsiveness. This heterogeneity increasingly motivates the development of multimodal and artificial intelligence-supported approaches in autism research. However, many existing approaches emphasize diagnostic classification, symptom prediction, or generic outcome modeling, while fewer frameworks explicitly preserve clinically interpretable constructs linking biological burden, developmental state, therapeutic accessibility, and responsiveness to intervention. This Hypothesis and Theory article proposes FIAP

Indexed as

artificial intelligenceautism spectrum disorderexplainable AImultimodal integrationneuroinformaticsprecision-stratified researchresponsible AItranslational stratification

Identifiers

PMID42746007
PMCPMC13574807

What OpenQuestion holds

Textmetadata
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.