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Skip search results from other journals and go to results- 7 Journal of Medical Internet Research
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Efficacy of eHealth Interventions for Hemodialysis Patients: Systematic Review and Meta-Analysis
J Med Internet Res 2025;27:e67246
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Predicting Age and Visual-Motor Integration Using Origami Photographs: Deep Learning Study
Second, we trained XGBoost 1.0.0 models (developed by Chen and Guestrin [17]) to use a child’s photo features to respectively predict the child’s age and raw VMI score. Res Net-50 extracted 2048 features from the photos and the XGBoost model predicted age and raw VMI scores. All combinations of the extracted photo features (from 1 photo alone to 8 photographs together) were respectively fitted to the XGBoost models.
JMIR Form Res 2025;9:e58421
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