Assessing dyslexia with machine learning: a pilot study utilizing Google ML Kit
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Tarih
2023-12-19
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, we explore the application of Google ML Kit, a machine learning development kit, for dyslexia detection in the Turkish language. We collected face-tracking data from two groups: 49 dyslexic children and 22 typically developing children. Using Google ML Kit and other machine learning algorithms based on eye-tracking data, we compared their performance in dyslexia detection. Our findings reveal that Google ML Kit achieved the highest accuracy among the tested methods. This study underscores the potential of machine learning-based dyslexia detection and its practicality in academic and clinical settings.
Açıklama
Anahtar Kelimeler
Dyslexia, Dyslexia detection, Eye movement data, Eyezenith, Face-tracking data, Google ML Kit, Supervised machine learning, Eye movements, Face recognition, Learning algorithms, Learning systems, Supervised learning, Dyslexium, Dyslexium detection, Eye movement datum, Face tracking, Google+, Supervised machine learning, Tracking data, Eye tracking
Kaynak
2023 Medical Technologies Congress (TIPTEKNO)
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Eroğlu, G. & Harb, M. R. A. (2023). Assessing dyslexia with machine learning: a pilot study utilizing Google ML Kit. Paper presented at the 2023 Medical Technologies Congress (TIPTEKNO), 1-4. doi:10.1109/TIPTEKNO59875.2023.10359236
