AI Implementation, Evaluation, and Safety Monitoring
Establishing frameworks for the safe deployment and longitudinal evaluation of AI in hospital and surgical environments, with performance validation and measurable clinical impact.
The AI Learning Lab: Advancing AI in Healthcare
A trusted partner for health care providers, health systems, and industry experts
The AI Learning Lab is Rutgers Health’s applied collaboration hub where interdisciplinary teams bridge cutting-edge research and real-world practice to integrate, validate, and build trustworthy AI healthcare solutions that deliver safer, more equitable patient-centered care.
Working together with RWJBarnabas Health, we engage with health care providers, administrators, analysts, operations teams, decision-makers, and other partners in New Jersey, nationally, and globally to develop innovative AI-based approaches to enhancing health care.
How We Work
The AI Learning Lab works to improve health care by partnering with health care providers and health systems, collaborating with interdisciplinary experts in clinical AI, and working with vendors to design and validate custom tools. Our approach emphasizes co-design, evaluation, and shared accountability.
- Partnering with providers and health systems
- Co-design workflows to pilot tools in real clinical settings
- Validate and measure impact on outcomes, safety, and clinician experience
- Collaborate with providers to guide AI development
- Collaborating with interdisciplinary experts in AI and healthcare
- Assemble clinicians, computer scientists, research experts, and informaticists
- Collaborate in to evaluate, validate, and build AI
- Apply Coalition for Health AI framework for transparency, equity, and resilience
- Working with technology vendors on AI solutions in healthcare
- Evaluate acquired AI tools for fit, safety, explainability, and local performance
- Partner on pilots, validation, and customization
- Provide feedback to improve tools for health system needs
Core Capacities
We help healthcare organizations move from promising concepts to proven impact. The AI Learning Lab supports the full lifecycle of AI and healthcare innovation — translating research into practice while ensuring transparency, performance, and accountability. Our core capacities include:
Explainable AI (XAI) and Clinical Trust
Advancing interpretable models that translate complex algorithmic outputs into transparent, actionable insights to build clinician confidence and support responsible decision-making.
AI-Enhanced Diagnostics and Clinical Oversight
Developing high-precision tools for complex imaging and neuroradiology that pair enhanced diagnostic accuracy with clear, human-understandable explanations for the care team.
Bias Mitigation, Fairness, and Equitable Care
Applying rigorous methodologies to detect and eliminate algorithmic bias, ensuring AI solutions promote health equity and expand access for diverse and underserved populations.
Precision Analytics and Multimodal Integration
Synthesizing diverse data streams to generate accurate, clinically relevant predictions that drive personalized patient care and optimize system-level strategic decisions.
Human–AI Collaboration and Workflow Optimization
Redesigning clinical workflows to harmonize the strengths of human expertise and machine intelligence, ensuring AI integration enhances provider experience and patient outcomes.
Case Studies
Examples from our early portfolio of work demonstrate how we collaborate with partners to translate innovation into meaningful clinical impact:
Epic Deterioration Index
This AI-powered early warning system helps care teams detect subtle signs that hospitalized patients’ conditions may be deteriorating—often hours before they become clinically obvious. Rigorous testing in our partner hospitals showed an 18.6% reduction in in-hospital mortality.
Implementation and Evaluation of AI in Surgery with Intuitive
In partnership with Intuitive, we support the implementation and real-world evaluation of AI-assisted surgical technologies. This work focuses on improving surgical precision, workflow efficiency, and patient safety.
Explainable Neuroradiology Support Tool
This AI-powered neuroradiology tool helps clinicians analyze complex brain imaging while providing clear explanations for its findings. By combining high diagnostic accuracy with strong explainability and interpretability features, the tool enhances clinical confidence, supports better decision-making, and includes built-in safety monitoring.
Partner With Us
The AI Learning Lab partners with organizations seeking responsible, credible pathways to AI innovation. Whether you are evaluating new tools, scaling validated solutions, or exploring how is AI used in healthcare in practice, we offer a collaborative, evidence‑driven approach grounded in real world impact.