// NeuroPred · Company · About Us
Meet NeuroPredPioneering Predictive Neuroimaging
We are a team of clinicians, neuroscientists, engineers, and data scientists united by one goal: turn uncertainty in neurocritical care into certainty. By combining advanced neuroimaging with predictive AI, we empower care teams to make faster, more informed decisions — improving outcomes and redefining what recovery can look like.
// Predict Outcomes, Empower Care
Our Mission
NeuroPred transforms neuroimaging into proactive intelligence — empowering clinicians to anticipate outcomes, intervene earlier, and deliver more precise care across the neurocritical team.
Above all, we are driven to give every patient the greatest opportunity to recover more completely and reclaim the life they cherish — returning home, to family, work, and independence with dignity and hope.
// 40+ Years in the Making
Our Journey
Pioneering neuroscience at the University of Iowa evolves into AI-driven predictions for neurocritical care.
// The People Behind the Platform
Our Leadership
Visionary clinicians, scientists, and operators united by a single mission — transforming stroke care through precision AI.
Powered by a World-Class Ecosystem
// Grounded in World-Class Science
Research Highlights
Building on pioneering work in lesion mapping, outcome prediction, and AI-driven neuroimaging from the University of Iowa Boes Lab.
Combined Citations by Founding Team
Demonstrating deep expertise in neuroimaging, lesion mapping, and predictive models for neurocritical care.
Our Scientific Origins
NeuroPred is built directly on groundbreaking research from the University of Iowa, in close collaboration with the Boes Lab — translating lesion-symptom mapping and predictive modeling into real-world neurocritical care tools.
Explore the Boes Lab at UIowa →
A Clinical Neuroimaging Platform for Rapid, Automated Lesion Detection and Personalized Post-Stroke Outcome Prediction
Michal Brzus, Joseph Griffis, Cavan J. Riley, Joel Bruss, Carrie Shea, Hans J. Johnson, Aaron D. Boes • 2025
This work presents a clinical neuroimaging platform that enables rapid, automated detection of brain lesions and personalized prediction of post-stroke functional and cognitive outcomes, supporting data-driven clinical decision-making.
Iowa Brain-Behavior Modeling Toolkit: An Open-Source MATLAB Tool for Inferential and Predictive Modeling of Imaging-Behavior and Lesion-Deficit Relationships
JC Griffis, J Bruss, SF Acker, C Shea, D Tranel, AD Boes • 2024
This work presents a MATLAB software toolkit that supports both inferential and predictive modeling frameworks, accommodates both classification and regression tasks, and includes a flexible and extensible model selection architecture.
Large-scale lesion symptom mapping of depression identifies brain regions for risk and resilience
Nicholas T Trapp, Joel E Bruss, Kenneth Manzel, Jordan Grafman, Daniel Tranel, Aaron D Boes • 2023
Large-scale lesion-symptom mapping identifies brain regions and networks linked to depression risk and resilience after focal brain lesions.
Post-stroke outcomes predicted from multivariate lesion-behaviour and lesion network mapping
Mark Bowren Jr, Joel Bruss, Kenneth Manzel, Dylan Edwards, Charles Liu, Maurizio Corbetta, Daniel Tranel, Aaron D Boes • 2022
These results support the notion that lesion location and lesion network mapping can be combined to improve the prediction of post-stroke deficits at 12-months.
// Next Step
Ready to Connect?
Let's Talk
You've seen what we stand for. Reach out to discuss partnerships, implementations, or how NeuroPred can support your team.