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Open Access

Peer-reviewed

Research Article

AI-driven approaches for dysgraphia diagnosis using online and offline handwriting data: A comprehensive scoping review

Avisa Fallah,

Roles Methodology, Validation, Visualization, Writing – original draft

Affiliation School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, Tehran, Iran
⨯
Yazdan ZandiyeVakili,

Roles Methodology, Validation, Visualization, Writing – original draft

Affiliation School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, Tehran, Iran
⨯
Hedieh Sajedi

Roles Conceptualization, Investigation, Methodology, Supervision, Validation, Writing – review & editing

* E-mail: hhsajedi@ut.ac.ir

Affiliation School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, Tehran, Iran

https://orcid.org/0000-0003-4782-9222

⨯

AI-driven approaches for dysgraphia diagnosis using online and offline handwriting data: A comprehensive scoping review

Avisa Fallah,
Yazdan ZandiyeVakili,
Hedieh Sajedi

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Published: December 31, 2025
https://doi.org/10.1371/journal.pone.0328722

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