aceToward early dyslexia screening through handwriting: A trustworthy XAI-enhanced deep learning framework
Dyslexia, a prevalent learning disorder, significantly impairs children's ability to process written language, often leading to challenges such as letter reversals, inconsistent spacing, and scrambled writing sequences. Early detection is critical for timely intervention, yet traditional diagnostic methods such as behavioral assessments and neuroimaging-are either time-consuming, subjective, or prohibitively expensive. Recent advances in deep learning offer promising alternatives, particularly through handwritin…
A CNN-GRU-Attention model with explainability tools classified dyslexic versus non-dyslexic handwriting at 99.5% accuracy, showing technical feasibility for a non-invasive, scalable screening approach.
The study used adolescents aged 12-15 with established diagnoses and has not been evaluated in younger, undiagnosed children, so it is not a validated early screening tool.
Evidence
- Peer-reviewedResearch in Developmental Disabilities2026-10-16
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Truvace Impact Record TRV-2026-1940, v1: “Toward early dyslexia screening through handwriting: A trustworthy XAI-enhanced deep learning framework.” Truvace, 2026-10-19. /record/TRV-2026-1940 (accessed at citation time). sha256 746be7217afe1b2e…
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