HIGHLIGHTS
- who: Eugenio Lomurno and colleagues from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy have published the research: Deep Learning and Procrustes Analysis for Early Dysgraphia Risk Detection with a Tablet Application, in the Journal: Life 2023, 13, 598. of /2023/
- what: Given this rationale, this paper presents an early dysgraphia classifier based on real, quantitative, and longitudinal data, developed through state-ofthe-art mathematical tools and deep learning techniques. The work showed how the Play-Draw-Write application can be complementary to expert observation, thus becoming a valuable aid in . . .
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