Data · dataset · 2026
Rabia Rao: EAIP-DARV: Ensemble AI for Early Autism Screening & Referral Support
Listed in ZivaHub
<p dir="ltr">Autism screening can be challenging when families face limited access, long pathways, cost barriers, and uncertainty about next steps.
Description
This research presents EAIP-DARV, an ensemble AI framework designed to support early autism screening and referral. The system integrates complementary AI models for screening, assessment, and correlation analysis, combining their predictions through an adaptive voting mechanism.
A disagreement-aware refinement and calibration stage further improves the reliability of prediction probabilities. In evaluation, EAIP-DARV achieved 82% accuracy and 88% sensitivity, with a Brier score of 0.138 and Expected Calibration Error (ECE) of 0.031. Its UAR reached 86.0%, representing improvements over conventional screening and existing AI approaches.
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The framework demonstrates the potential of accessible, data-driven AI to support earlier screening and clearer referral pathways, while clinical assessment remains central to diagnosis.</p>
Links
Where it is published
- DOI doi.org/10.17608/k6.auckland.34005774.v2 ↗
DOI / persistent id · from zivahub uct ac za
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from zivahub uct ac za
Topics
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ZivaHub | oai:figshare.com:article/34005774 | 5 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
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| concepts[field].anzsrc:field:461103 | mapping · zivahub uct ac za | vocabulary-mapper@1.0.0 | keywords['Deep learning'] |
| concepts[field].anzsrc:field:461106 | mapping · zivahub uct ac za | vocabulary-mapper@1.0.0 | keywords['Semi- and unsupervised learning'] |
| concepts[field].anzsrc:group:4602 | mapping · zivahub uct ac za | vocabulary-mapper@1.0.0 | keywords['artificial intelligence'] |
| concepts[field].anzsrc:group:4611 | mapping · zivahub uct ac za | vocabulary-mapper@1.0.0 | keywords['machine learning'] |
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| concepts[field].local:field:earth-environmental | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| description | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/description |
| license | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/rights |
| publication_date | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| title | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/title |