Multimodal Depression Detection Based on Self-Attention Network With Facial Expression and Pupil.

Decomposing Neuroanatomical Heterogeneity of Autism Spectrum Disorder Across Different Developmental Stages Using Morphological Multiplex Network Model.

DepMSTAT: Multimodal Spatio-Temporal Attentional Transformer for Depression Detection.

Wearable Eye-Tracking System for Synchronized Multimodal Data Acquisition.

Behavioral Information Feedback With Large Language Models for Mental Disorders: Perspectives and Insights.

Heterogeneous Graph Attention Networks for Depression Identification by Campus Cyber-Activity Patterns.

Aim Where You Look: Eye-Tracking-Based UAV Control Framework for Automatic Target Aiming.

Depressive semantic awareness from vlog facial and vocal streams via spatio-temporal transformer.

Are Large Language Models Possible to Conduct Cognitive Behavioral Therapy?

Clustering Based on Eye Tracking Data for Depression Recognition.

Detecting depression based on facial cues elicited by emotional stimuli in video.

Retinal Vessel Segmentation in Medical Diagnosis using Multi-scale Attention Generative Adversarial Networks.

Orthogonal-Moment-Based Attraction Measurement With Ocular Hints in Video-Watching Task.

Filterable sample consensus based on angle variance for pupil segmentation.

Undisturbed Mental State Assessment in the 5G Era: A Case Study of Depression Detection Based on Facial Expressions.

Independent Encoder for Deep Hierarchical Unsupervised Image-to-Image Translation.

MODMA dataset: a Multi-model Open Dataset for Mental-disorder Analysis.