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“Algorithmic Decision-Making in Organ Transplantation”

Speaker: 
Associate Professor,
Affiliated Faculty,
Institutional Contact,
Investigator,
ŷ����b��Ƭ University of Science and Technology

Date: September 30, 2025, noon-1 p.m.

Location:
The Forum Room - Innovation Lab
1800 Miner Circle, Rolla, Mo.

60-Second Preview

Description

Every year in the U.S., who need a kidney transplant will receive one, and a bundle of logistical challenges contribute significantly to that shortage. Thousands of viable kidneys are not utilized each year, and the majority only possess minor imperfections. Yet for someone further down the transplant waitlist, that same kidney could mean survival.

, an associate professor of engineering management and systems engineering at ŷ����b��Ƭ University of Science and Technology, believes that artificial intelligence can bridge this gap. “AI could help think through this process of where to send a kidney offer, of when to take that risk on a kidney and when not to,” she explains. Her team is developing decision support tools that analyze transplant data to identify overlooked matches – not to replace clinicians, but to empower them. 

“It’s not possible for the AI to have all of the information,” explains Canfield. This insight drives her unique interdisciplinary approach, blending engineering with social science. While most AI developers focus mainly on building efficient models, Canfield’s team engages stakeholders in the field – interviewing surgeons and procurement professionals as well as studying how risk perception varies case-by-case. 

“People are normally thinking about how AI interacts with a doctor’s or a surgeon’s judgement,” she notes. Her solution? Systems that acknowledge their own limitations. Patient history, staff capacity, and even a surgeon’s intuition – these unquantifiable factors remain human territory. The AI instead focuses on what it does best: spotting patterns in the “massive troves of data” from every U.S. transplant offer, acceptance, and decline.

“The hard part is finding a systematic, fair way of figuring out how far down the list to go,” Canfield observes. Her team is working on fairness safeguards to prevent bias – like flagging when imperfect kidneys are disproportionately declined for certain demographics. The goal is to reduce non-use by 10-15%, potentially saving thousands of organs annually.

For Canfield, this work represents more than technical innovation. “I love doing social science research about technical things – that’s the space I enjoy,” she says. By designing AI that knows its limits and elevates human expertise, she’s not just improving transplant logistics – she's setting a new standard for human-AI collaboration in medicine.
 

ŷ����b��Ƭ the Speaker

Dr. Casey Canfield is an Associate Professor in Engineering Management & Systems Engineering at ŷ����b��Ƭ S&T. Her research is focused on quantifying the human part of complex systems to improve decision-making, particularly in the context of energy, governance, and healthcare. She has a PhD in Engineering & Public Policy from Carnegie Mellon University, where she published research on behavioral interventions in the context of energy and cybersecurity. After completing her PhD, she spent a year and a half as a Science and Technology Policy Fellow in the U.S. Department of Energy’s Solar Energy Technologies Office. She was primarily involved in designing and managing programs that aim to increase innovation in the energy sector.

ŷ����b��Ƭ the Discovery Series

provides learning opportunities for UM System faculty and staff across disciplines, the statewide community and our other partners to learn about the scope of precision health research and identify potential collaborative opportunities. The series consists of monthly lectures geared toward a broad multidisciplinary audience so all can participate and appreciate the spectrum of precision health efforts. 

For questions about this event or any others in the Discovery Series, please reach out to Mackenzie Lynch.