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Virtual Reality-Assisted Prediction of Adult ADHD based on Eye Tracking, EEG, Actigraphy and Behavioral Data: A Machine Learning Analysis of Independent Training and Test Samples
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Category: Data
Description: This project investigates the predictive utility of multimodal data, including eye-tracking, EEG, actigraphy, and behavioral indices, in classifying adults with ADHD compared to healthy individuals. Using a support vector machine model, we analyzed independent training (n=50) and test samples (n=36). In both studies, participants performed a continuous performance task in a virtual reality seminar room while being confronted with virtual distractions.
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