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Accessible Healthcare Through AI- Augmented Decisions (AHeAD) Center

A Planned National Science Foundation Industry-University Cooperative Research Center

The center is a collaboration between the University of Louisiana at Lafayette, Tulane University, the University of Florida, Georgia Tech, and Tampere University.

NSF AHeAD brings university researchers with healthcare industry stakeholders to conduct foundational research needed to create usable AI-augmented decision support tools that enhance healthcare delivery, improve patient outcomes, and reduce costs.

The AHeAD center addresses research gaps to make AI-Augmented systems safer and more usable across health systems. Even with significant promise in AI to improve care delivery and controlling costs, organizations face barriers to safe and effective implementation, including concerns about AI accuracy, patient safety and integration with health system workflows. AHeAD brings together leading AI researchers with implementation experts to address these challenges related to Human-AI interaction, privacy preserving AI and robustness of AI models.

The center will create best practices, evaluation frameworks, open models, and practical toolkits that health organizations can use to deploy AI systems more safely and effectively, train next-generation AI healthcare specialists, accelerating industry-wide adoption.

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View press release

Interdisciplinary Foundations

AI/Machine Learning 

Human-Computer Integration 

Data Science & Systems Engineering 

Implementation Science

Clincial and Public Health 

Evaluation Science

Research Focus Areas

Human-AI Integration - How to improve the explainability and transparency of AI models for users?

Creating explainable AI systems with transparent decision pathways that enable patients, providers, and public health officials to understand and trust AI across multiple contexts, including patient education, clinical decision support, and population health management.

Privacy Preserving AI - How to improve generalizability of AI models across facilities while preserving confidentiality and privacy?

Advancing AI models that work across diverse populations and healthcare settings through federated learning, differential privacy, and secure computation – enabling multi-institutional collaboration and research while maintaining patient privacy and regulatory compliance.

Accessible Health Technologies - How to make AI-augmented healthcare accessible by all populations?

Designing AI-augmented telehealth and remote care solutions for rural and geographically isolated populations through low-bandwidth platforms, accessible interfaces, and user-centered design – overcoming barriers of distance, connectivity, and digital literacy.

High Confidence AI Models - How do we improve the confidence of AI models when multiple systems are integrated?

Ensuring reliable, validated AI performance across clinical and operational applications through rigorous testing frameworks, uncertainty quantification, continuous monitoring, and robust handling of edge cases and model drift in safety-critical healthcare decisions.

What is a NSF Industry University Cooperative Research Center?


The IUCRC program accelerates the impact of basic research through close relationships between industry innovators, world-class academic teams, and government leaders. IUCRCs are designed to help corporate partners and government agencies connect directly and efficiently with university researchers.

Visit IUCRC.NSF.GOV for more information.

Partner with the AHeAD Center to create next-generation AI-augmented healthcare decision-support tools for your organization.

You are welcome to download and share the center overview document. (View PDF) 

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