NeuroCypher ASD: Machine Learning with Knowledge Graph-Based Representation for ASD Screening in Toddlers
Georgios Bouchouras, Dimitrios Doumanas, Konstantinos Kotis · 2026
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Description
Georgios Bouchouras, Dimitrios Doumanas and Konstantinos Kotis present in 2026 NeuroCypher ASD, a screening framework for autism in toddlers that pairs questionnaire-based prediction with a knowledge graph for exploration. Standard questionnaire scores can be hard to interpret and compare across cases.
A tabular model estimates risk from answers and demographics, while the graph organises cases for comparison, pattern browsing and plain-language querying. Leakage-aware testing compared tabular, graph and hybrid variants, finding the tabular model strongest for pure prediction. Explanation tools map model reasoning back to questionnaire items, while an anomaly module flags unusual cases for closer human review.
Catalog record
| CREATOR | Georgios Bouchouras, Dimitrios Doumanas, Konstantinos Kotis |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 61612 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |