Team Visit to Mid-America Transplant

Several members of our team recently had the opportunity to visit Mid-America Transplant, where we presented our progress. Following the meeting, we toured their facilities to gain a deeper understanding of their operational processes and what goes on behind the scenes. This visit provided important insights that will inform our design approach for the upcoming SimUNet trial. We are grateful to MidAmerica Transplant for their time and ongoing collaboration.  

Dr. Casey Canfield, Grace Hall, and Amaneh Babaee outside the MidAmerica Transplant office. Not pictured: Dr. Cihan Dagli. 

Honorable Mention for Best Poster at IEEE Ethics Conference 2025 

On June 7th, Dr. Casey Canfield presented a poster at the IEEE Ethics Conference 2025 titled “Improving System-Level Outcomes via Artificial Intelligence Decision Support in Kidney Utilization.” Her work received an honorable mention award for best poster. 

The poster highlighted: 

  • The motivation behind using AI to improve kidney utilization decisions 
  • Details of our AI model and its usability 
  • Considerations around potential AI bias 
  • A projected path for AI adoption in clinical decision-making 
  • Plans for a randomized control trial using SimUNet scheduled for January 2026 

This work is part of a larger interdisciplinary effort to bridge engineering, medicine, and ethics in support of better transplant outcomes. This recognition reflects ongoing efforts to enhance organ transplantation outcomes through ethical and impactful AI applications. . 

Dr. Casey Canfield presenting her poster, “Improving System-Level Outcomes via Artificial Intelligence Decision Support in Kidney Utilization,” at the IEEE Ethics Conference 2025. 
Dr. Casey Canfield receiving an Honorable Mention for Best Poster at the IEEE Ethics Conference 2025 held at Northwestern University. 

The National Innovation Forum – The Alliance

At the National Innovation Forum hosted by The Alliance, Dr. Casey Canfield from Missouri S&T presented our team’s work on designing appropriate AI for organ allocation and acceptance—AI that not only predicts outcomes but also aligns with the real-world needs of transplant stakeholders.

She summarized the three deep learning models that help predict organ utilization, provisional acceptance, and final acceptance. These tools aim to support both Organ Procurement Organizations (OPOs) and transplant centers, particularly in time-sensitive or uncertain decision scenarios.

The core focus of the presentation was that AI must be fair and explainable. The team is actively investigating bias in training data to incorporate stakeholder input to define fairness more inclusively. She also highlighted the importance of explainable AI (XAI) to help users understand and trust the system.

This work is building toward a 2026 field trial using SimUNet, a behavioral science platform that mimics real-world transplant decision-making environments.

To see Dr. Canfields full presentation slides, please click below.

You can watch Dr. Canfield’s presentation—along with the full day of sessions—here!