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However, machine learning-based assessment faces significant challenges due to limited labeled data and label quality, introducing uncertainties in the model.
However, machine learning-based assessment faces significant challenges due to limited labeled data and label quality, introducing uncertainties in the model.
Official repository for paper "Modeling Uncertainty in Computer Vision based Gross Motor Function Assessment of Children with Cerebral Palsy".
Sep 8, 2024 · Hermano Igo Krebs · View · Modeling Uncertainty in Computer Vision Based Gross Motor Function Assessment of Children with Cerebral Palsy.
The proposed AI-based GMFCS Assessment is much more convenient, faster, and cheaper than conventional evaluation. Recent progress in the field of machine ...
We propose an end-to-end model, achieving an accuracy rate of approximately 76.6% in assessing children with Cerebral Palsy (CP) using the Gross Motor Function ...
Missing: Uncertainty | Show results with:Uncertainty
Sep 6, 2022 · Action observation treatment improves upper limb motor functions in children with cerebral palsy: a combined clinical and brain imaging study.
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8 days ago · There is, therefore, a need to develop automated early pre- screening tools that can detect atypical patterns of motor development before they ...
Jul 8, 2010 · The aim of this study was to investigate the predictive value of a computer-based video analysis of the development of cerebral palsy (CP) in young infants.
Jul 11, 2022 · This study's findings suggest that deep learning–based assessments could support early detection of CP in infants at high risk.