APS
2026 APS Annual Convention
Precision Mental Health with Intensive Longitudinal Data and Machine Learning: From Neuroimaging to Ecological Behavior
This symposium integrates neuroimaging, ecological momentary assessment, and actigraphy with modern machine learning to advance precision mental health. Presenters examine neural, cognitive, and behavioral indicators of anxiety and depression, evaluate idiographic models, and test person-specific prediction tools for community dwelling adults. Applications emphasize scientific, clinical, and translational relevance.
Chairs & Discussants
- Nur Hani ZainalChair
National University of Singapore
Presentations
- Integrating Group-Level Patterns for Individual-Level Inference: A Framework for Idionomic Approaches In Psychological ScienceStephanie Noble
- Machine Learning In the Prediction of Treatment Response for Emotional Disorders: A Systematic Review and Meta-Analysis Joshua Curtiss
- Sleep and Anxiety Dysregulation As Distal Risk Pathways: Machine Learning Evidence from Four Nine-Year Longitudinal CohortsNur Hani Zainal
