Mayo Clinic AI Summit

Introducing the 2026 AI Summit!

We are pleased to invite you to participate in the AI Summit conference titled “AI Summit: A New Engine for Real-World Evidence Generation: Multi-Agentic AI and Simulation” to be held in Rochester, Minnesota on June 4-5, 2026. The conference is organized by the Mayo Clinic Department of Artificial Intelligence and Informatics in partnership with the Mayo Clinic Research Shield and the Mayo Clinic AI community.

The rapid advancement of large language models has transformed how medical evidence can be captured, interpreted, and generated. Building upon this foundation, multi-agentic AI enables intelligent coordination and reasoning across complex, data-rich tasks—amplifying the capacity of AI systems to manage scale and complexity. Through simulation frameworks, these models can move beyond analyzing what has been observed to reasoning about and generating evidence for scenarios that have not yet occurred. Together, multi-agentic AI and simulation establish a new paradigm for real-world evidence generation—linking data, reasoning, and virtual experimentation to create insights that are both generalizable and clinically meaningful.

You are invited to submit proposals to be considered for presentation through the conference registration and submission website. 

Registration will open February 2, 2026.

Abstract Submission:

We invite the submission of abstracts to be considered for the following presentation types and topic areas:

The abstract submission window is open through February 27, 2026

SUBMIT ABSTRACT

Presentation Types:


 Lightning Talk (10 minutes)

 Poster Presentation

 Workshop/Tutorial (1.5 and 3 hour blocks available)

Lightning Talk & Poster Abstract Submission Template:

Download template

Workshop / Tutorial Abstract Submission Template:

Download template

Publication Opportunity:

Top 15 abstracts will be selected for publication in Mayo Clinic Proceedings - Digital Health, and a subset of them will be invited for expansion into full articles and be peer-reviewed.

Topics:

1.    Multi-Agent and Autonomous Clinical Intelligence

  • Multi-agent systems for clinical reasoning, coordination, and decision support
  • Autonomous orchestration of tools, policies, and workflows with human-in-the-loop oversight
  • Federated or decentralized intelligence with centralized reasoning and auditability
  • Conflict resolution, uncertainty modeling, and safety-aware agent behaviors


2.    Simulation, Digital Twins, and Virtual Biology

  • Clinical trial emulation and counterfactual simulation using real-world data
  • Patient-, cohort-, and population-level digital twins
  • Virtual organs, cells, and biological systems for mechanism discovery and toxicology
  • Simulation-based evaluation of trial designs, interventions, and care pathways

 
3.    Multimodal Foundation Models and Computing Systems Infrastructure

  • Foundation models for multimodal clinical data (EHR, imaging, genomics, signals)
  • Knowledge-augmented AI using ontologies, knowledge graphs, and structured evidence
  • Multimodal reasoning across text, images, time-series, and biological data
  • Domain adaptation, fine-tuning, and transfer learning for healthcare applications
  • Robotics as a foundational computational and embodied intelligence layer
  • Quantum computing, high-performance computing, and specialized hardware

 
4.    Responsible, Evaluated, and Deployable AI

  • Rigorous evaluation, benchmarking, and real-world validation of AI systems
  • Fairness, robustness, generalizability, and transportability across populations
  • Community engagement, clinician-in-the-loop design, and participatory evaluation
  • Governance, auditability, safety monitoring, and regulatory readiness

 
5.    Clinical and Translational Applications

  • Precision medicine and patient stratification
  • Real-world evidence generation and learning health systems
  • Clinical decision support and workflow integration
  • Surgical and interventional translation
  • Translation of AI methods into practice and policy