Digital Mental Health & AI Symposium
Poster Session 2023
Participants
Madhusudan Basak
Understanding treatment information needs from social media for opioid recovery
Vafa Batool
Therapy for Therapists: Design Opportunities to Support the Psychological Well-being of Mental Health Workers
Zequn (Vincent) Chen
Fair ordinal regression prediction of medical students’ anxiety
Susobhan Ghosh
MiWaves: AI-based mobile health intervention to reduce cannabis use amongst emerging adults
Michael Heinz
Detecting the Use of Antidepressants with Passively Collected Wearable Movement Data and Deep Learning in a Nationally Representative Sample
Frances Koback, Vincent Busque, Thomas Thesen
Leveraging Wearable Data and Machine Learning to Enhance Student Well-Being in Medical Education
Daniel Mackin
Neuromelanin, Reinforcement Learning, and Anhedonia: Identifying Associations, Antecedents, and Consequences
Subigya Nepal
MoodCapture: Depression Detection Using In-the-wild Smartphone Images
Arvind Pillai
Investigating Generalizability of Speech-based Suicidal Ideation Detection Using Mobile Phones
George Price
Predicting Future MDD Symptom Variability With Passively-Collected Wearable Movement Information In A Clinical Population: A Machine Learning Approach
Mark Rucker
CAMSA: Context-Aware Micro-interventions for Social Anxiety
Omar Sharif
Characterizing Information Seeking Events in Health-Related Social Discourse
Tinashe Tapera
Continuous Stress Monitoring in Real-World
Zhiyuan Wang
Detecting Social Contexts from Mobile Sensing Indicators in Virtual Interactions with Socially Anxious Individuals