Rochester, Minn.-based Mayo Clinic is moving beyond predictive AI models toward systems that support clinical decision-making, health system leaders said at its recent AI Research Summit.
More than 750 researchers, clinicians, AI scientists and engineers attended the June 4-5 event in Rochester and online.
“The future of healthcare AI is not simply about building better predictor models, it’s about developing integrated decision-intelligence systems,” Cui Tao, PhD, the Nancy Peretsman and Robert Scully Chair of AI and Informatics at Mayo Clinic, said at the event, per a June 29 news release.
Speakers highlighted multiagentic AI, where several AI agents collaborate on complex tasks, and simulations that use real-world data to test hypotheses faster than traditional research methods. Yong Chen, PhD, of Philadelphia-based University of Pennsylvania, said clinicians need tools that recommend next steps — such as optimal timing for antiplatelet therapy after a stent procedure — not just risk scores.
Matt Redlon, chair of Mayo Clinic’s AI program and vice president of digital biology, said multiagentic systems could help researchers screen existing drugs for repurposing and run AI-simulated virtual trials to generate early efficacy signals.
Micky Tripathi, PhD, Mayo Clinic’s chief AI implementation officer, said healthcare organizations still need to build governance and infrastructure around AI tools, comparing the work to adding a chassis and steering wheel to an engine.
The summit underscores Mayo Clinic’s position at the center of AI research investment, following the health system’s recent collaboration with Microsoft to build a frontier AI model for clinical use.
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