Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...
Objective: This study compared a conventional logistic regression model with machine learning (ML) models using demographic and clinical data to predict outcomes at 2 and 6 months of treatment for MDR ...
Mary Ton is an assistant professor and digital humanities librarian at the University of Illinois. In her own research and ...
This study presents valuable findings by reanalyzing previously published MEG and ECoG datasets to challenge the predictive nature of pre-onset neural encoding effects. The evidence supporting the ...
Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).
Abstract: Advancements in machine learning (ML) and artificial intelligence (AI) have paved the way for the deepfake spectrum to expand in the tech space. The growing demand for generative AI has ...
Abstract: Deep neural networks (DNNs) deliver strong speech enhancement (SE) but can degrade under domain shift, whereas classical signal processing remains robust yet limited for highly ...
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