Project scaffold
Multimodal biomarkers and digital phenotyping
Theme focused on bringing together imaging, behavioral, clinical, and digital data to support interpretable models in behavioral health.
Problem Space
Behavioral health research often depends on fragmented data sources that do not naturally align. Imaging, symptoms, outcomes, and digital signals each provide partial views, making integration and interpretation a central challenge.
Approach
This project area focuses on multimodal data integration, longitudinal modeling, digital phenotyping, and clinically grounded analytical workflows that prioritize interpretability and research usefulness over unnecessary complexity.
Collaborators
Suitable collaborators include groups working on clinical datasets, wearables, digital mental health, multimodal analysis, or biomarker development.
Next Steps
Future content can include example data structures, project pages for specific datasets, and updates on clinically relevant biomarker questions.
Contact
Strong inquiries in this area should describe the available data modalities, the decision problem, and any real-world deployment or validation constraints.