Location
Havener Center, Miner Lounge / Wiese Atrium, 9:30am-11:30am
Start Date
4-2-2026 9:30 AM
End Date
4-2-2026 11:30 AM
Presentation Date
April 2, 2026; 9:30am-11:30am
Description
Approximately 30% of deceased-donor kidneys remain unused, representing missed opportunities for transplantation. One potential solution is identifying hard-to-place kidneys earlier in the allocation process to reduce late-stage reassessment and allocation inefficiencies. Over a four-year project, our team developed an artificial intelligence (AI) algorithm that provides Organ Procurement Organization (OPO) coordinators with an AI score indicating the likelihood that a kidney will be transplanted. This study evaluates the impact of this AI score on kidney placement decisions. Using a pre–post experimental design, participants will first evaluate four donor kidneys without AI support. After watching a training video explaining the AI score, they will evaluate four additional kidneys with AI assistance. In each case, participants assess kidneys at two stages of information availability and report perceptions of hard-to-place status, workload, and confidence. We hypothesize that the AI score will improve early identification of hard-to-place kidneys, reduce decision time, and decrease coordinators’ perceived workload.
Biography
Amaneh Babaee obtained her Bachelor of Science in Industrial Management in 2012 and her Master of Science in Business Administration in 2015 from Kar Higher Education Institute. Upon graduating, she started working as a Human Resource Generalist at Acco Furniture which made her eager to expand her knowledge related to organization operations. As a result, Amaneh started her Master of Science in Industrial-Organizational Psychology at Missouri University of Science and Technology in 2023. During her graduate program, she contributed to an interdisciplinary research project where different expertise from different departments collaborated to address real-world needs and challenges regarding AI systems. She particularly focus on AI use in transplant system. This work encouraged her to start her PhD program in Social/IO Psychology in June 2025. In addition to her Publishing Academy certificate, she published her research in different prestigious journals such as Digital Health and Discover Artificial Intelligence.
Meeting Name
2026 - Miners Solving for Tomorrow Research Conference
Department(s)
Psychological Science
Document Type
Poster
Document Version
Final Version
File Type
event
Language(s)
English
Rights
© 2026 The Authors, All rights reserved
Included in
Measuring the Influence of AI Decision Support on Organ Procurement Coordinators’ Workflow
Havener Center, Miner Lounge / Wiese Atrium, 9:30am-11:30am
Approximately 30% of deceased-donor kidneys remain unused, representing missed opportunities for transplantation. One potential solution is identifying hard-to-place kidneys earlier in the allocation process to reduce late-stage reassessment and allocation inefficiencies. Over a four-year project, our team developed an artificial intelligence (AI) algorithm that provides Organ Procurement Organization (OPO) coordinators with an AI score indicating the likelihood that a kidney will be transplanted. This study evaluates the impact of this AI score on kidney placement decisions. Using a pre–post experimental design, participants will first evaluate four donor kidneys without AI support. After watching a training video explaining the AI score, they will evaluate four additional kidneys with AI assistance. In each case, participants assess kidneys at two stages of information availability and report perceptions of hard-to-place status, workload, and confidence. We hypothesize that the AI score will improve early identification of hard-to-place kidneys, reduce decision time, and decrease coordinators’ perceived workload.
Comments
Advisor: Daniel Burton Shank, shankd@mst.edu