5 citations · 14 across the 5 of their papers we have counts for
5 papers
MIND: Empowering Mental Health Clinicians with Multimodal Data Insights through a Narrative Dashboard
Ruishi Zou, Shiyu Xu, Margaret E Morris +11
Advances in data collection enable the capture of rich patient-generated data: from passive sensing (e.g., wearables and smartphones) to active self-reports (e.g., cross-sectional…
Neural Mixed Effects for Nonlinear Personalized Predictions
Torsten Wörtwein, Nicholas Allen, Lisa B. Sheeber +3
Personalized prediction is a machine learning approach that predicts a person's future observations based on their past labeled observations and is typically used for sequential ta…
Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework
Paul Pu Liang, Yun Cheng, Xiang Fan +9
The recent explosion of interest in multimodal applications has resulted in a wide selection of datasets and methods for representing and integrating information from different mod…
Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data
Paul Pu Liang, Terrance Liu, Anna Cai +7
Mental health conditions remain underdiagnosed even in countries with common access to advanced medical care. The ability to accurately and efficiently predict mood from easily col…
Multimodal Privacy-preserving Mood Prediction from Mobile Data: A Preliminary Study
Terrance Liu, Paul Pu Liang, Michal Muszynski +5
Mental health conditions remain under-diagnosed even in countries with common access to advanced medical care. The ability to accurately and efficiently predict mood from easily co…