TY  - JOUR
AU  - Bernárdez Vilaboa, Ricardo
AU  - Povedano Montero, Francisco Javier
AU  - Trillo, José Ramón
AU  - Ruiz Pomeda, Alicia
AU  - Martínez Florentín, Gema
AU  - Cedrún Sánchez, Juan Enrique
PY  - 2025
DO  - 10.3390/photonics12070711
UR  - https://hdl.handle.net/20.500.14352/123225
T2  - Photonics
AB  - Background/Objective: This study aims to evaluate the predictive performance of three supervised machine learning algorithms—decision tree (DT), support vector machine (SVM), and k-nearest neighbors (KNN) in forecasting key visual skills relevant to...
LA  - eng
PB  - MDPI
KW  - Eye tracking
KW  - Machine learning
KW  - Visual performance
KW  - Rhythmic gymnastics
KW  - Decision tree classification
KW  - Biomedical optics
TI  - AI-Based Prediction of Visual Performance in Rhythmic Gymnasts Using Eye-Tracking Data and Decision Tree Models
TY  - journal article
ER  -