AI-Ready Data & Software
A neuroinformatics hub generating powerful integrative data from home-grown software tools that enrich our tissue and data reserves. The age of AI is upon us but to take full advantage of AI, we need good data.
The Platform
Intuition harmonizes many types of data clinical, radiological, physiological, histological, and molecular against the exact tissue each came from, in a standardized, AI-ready structure. Contact us for data sharing.
Intuition Modules
Federated human epilepsy surgery brain tissue biobank and data the Chicago Epilepsy Collaboration Program.
Natural history and a personalized health approach to care for rare brain disorders.
Integrating Neuro ICU data to discover and validate new biomarkers.
Automating the neuropsychology testing workflow to build AI-ready datasets.
Also in the pipeline: nerve injuries and neuroinflammation in patients with ALS.
Inside the Platform
Browse and query clinically linked tissue and multimodal data in one place.
Longitudinal natural-history views for rare brain disorders such as Sturge-Weber Syndrome.
Real-time integration of neuro-intensive-care data for biomarker discovery.
How the modules connect across the tissue-to-data-to-discovery lifecycle.
Self-service research cohort identification and data retrieval for the UIC Clinical Research Data Warehouse. ADRESai is a multimodal informatics platform built to harmonize diverse data types, improve efficiency, and expand core operations to help the UIC research community request and process clinical data.
It expedites and automates cohort identification, data availability, the IRB process, and data extraction and integrates and connects many types of siloed data in a standardized way, making it ideal for AI and machine learning.
A tool for estimating postmortem-interval–driven gene expression changes foundational to why our rapid autopsy program matters. (Migrating to this site soon.)
Our AI-ready, disease-specific datasets are available to collaborators. Contact us to discuss access and partnership.