Predicting Age and Visual-Motor Integration Using Origami Photographs: Deep Learning Study
Our findings indicate that AI techniques have a significant potential for predicting children's development. The insights provided by AI may assist therapists in better interpreting children's performance in activities.
Authors
- Ching‐Lin Hsieh (ORCID: https://orcid.org/0000-0001-9468-9969)
- Jenn-Jier James Lien (ORCID: https://orcid.org/0000-0003-3944-7523)
- Gong‐Hong Lin (ORCID: https://orcid.org/0000-0001-6369-7165)
- Yen‐Ting Yu (ORCID: https://orcid.org/0000-0002-5967-8655)
- Kuan‐Lin Chen (ORCID: https://orcid.org/0000-0001-9996-814X)
- Chien-Yu Huang (ORCID: https://orcid.org/0000-0002-4024-9906)
Institutions
- Asia University (TW)
- National Taiwan University (TW)
- National Taiwan University Hospital (TW)
- National Cheng Kung University Hospital (TW)
- Taipei Medical University (TW)
- National Cheng Kung University (TW)
Publication Details
- Journal
- JMIR Formative Research
- Published
- 2025-01-10
- DOI
- https://doi.org/10.2196/58421
- Primary Topic
- Tactile and Sensory Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00