32 citations · 120 across the 18 of their papers we have counts for
6 papers · 1 filter
Learning Oculomotor Behaviors from Scanpath
Beibin Li, Nicholas Nuechterlein, Erin Barney +9
Identifying oculomotor behaviors relevant for eye-tracking applications is a critical but often challenging task. Aiming to automatically learn and extract knowledge from existing…
Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis
Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek +4
Understanding how certain brain regions relate to a specific neurological disorder has been an important area of neuroimaging research. A promising approach to identify the salient…
Invertible Network for Classification and Biomarker Selection for ASD
Juntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li +2
Determining biomarkers for autism spectrum disorder (ASD) is crucial to understanding its mechanisms. Recently deep learning methods have achieved success in the classification tas…
A Facial Affect Analysis System for Autism Spectrum Disorder
Beibin Li, Sachin Mehta, Deepali Aneja +4
In this paper, we introduce an end-to-end machine learning-based system for classifying autism spectrum disorder (ASD) using facial attributes such as expressions, action units, ar…
Efficient Interpretation of Deep Learning Models Using Graph Structure and Cooperative Game Theory: Application to ASD Biomarker Discovery
Xiaoxiao Li, Nicha C. Dvornek, Yuan Zhou +3
Discovering imaging biomarkers for autism spectrum disorder (ASD) is critical to help explain ASD and predict or monitor treatment outcomes. Toward this end, deep learning classifi…
Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI
Xiaoxiao Li, Nicha C. Dvornek, Juntang Zhuang +2
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder. Finding the biomarkers associated with ASD is extremely helpful to understand the underlying roots of the d…