Prototypes
Deceased Donor Kidney Assessment
Webinars
2023, Aug 1, 6-7pm CT. AI in Kidney Acceptance Research Update Webinar, Online. [Slides]
Journal Publications
Subramanian, H. V. , Canfield, C., & Shank, D. B. (2024). Designing Explainable AI to Improve Human-AI Team Performance: A Medical Stakeholder-Driven Scoping Review. Artificial Intelligence in Medicine. https://doi.org/10.1016/j.artmed.2024.102780
Subramanian, H. V., Canfield, C., Shank, D. B., & Kinnison, M. (2023). Combining Uncertainty Information with AI Recommendations Supports Calibration with Domain Knowledge. Journal of Risk Research, 26(10), 1137-1152. https://doi.org/10.1080/13669877.2023.2259406
Ashiku, L. & Dagli, C. (2023). Identify Hard-to-Place Kidneys for Early Engagement in Accelerated Placement With a Deep Learning Optimization Approach. Transplantation Proceedings, 55(1), 38-48. https://doi.org/10.1016/j.transproceed.2022.12.005
Elder, H., Canfield, C., Shank, D. B., Rieger, T., & Hines, C. (2022). Knowing When to Pass: The Effect of AI Reliability in Risky Decision Contexts. Human Factors , 66(2), 348-362. https://doi.org/10.1177/00187208221100691
Threlkeld, R., Ashiku, L., Canfield, C., Shank, D., Schnitzler, M., Lentine, K., Axelrod, D., Battineni, A. C. R., Randall, H., Dagli, C. (2021). Reducing Kidney Discard with Artificial Intelligence Decision Support: The Need for a Transdisciplinary Systems Approach. Current Transplantation Reports, 8, 263-271. https://doi.org/10.1007/s40472-021-00351-0
Conference Proceedings
Dzieran, R., Dagli, C., Marley, R. (2025). Human–AI Teaming in Complex Healthcare Systems: A Fuzzy Associative Memory Approach Integrating Surgeon Expertise and Deep Learning Models. Council of Engineering Systems Scholars and Universities, Arlington, VA.
Canfield, C., Dagli, C., Chank, D. B., Lentine, K., Schnitzler, M., Randall, H., Nadendla, V. S. S. & Cummiskey, B. (2025). Improving System-Level Outcomes via Artificial Intelligence Decision Support in Kidney Utilization. IEEE International Symposium on Ethics in Engineering, Science, and Technology (ETHICS), Evanston, IL. *Awarded Honorable Mention, Best Poster Award. [Blog post]
Dzieran, R., Threlkeld, R., Ashiku, L., Canfield, C., Dagli, C., Marley, R., J., Lentine, K., Randall, H., Schnitzler, M., Levanos, T., Rothweiler, R., Speir, L., and Marklin, G. (2024). Fuzzy Associative Memory and Deep Learning Network Model Interface with Transplant Surgeon in Assessing Hard-to-Place Kidneys for Use in Digital Twin Model. American Journal of Transplantation, 24(6), s1. (extended abstract published from American Transplant Congress) *Awarded “Best of Show” Ribbon. [Blog post]
Threlkeld, R., Ashiku, L., Dzieran, R., Sandeep, M., Canfield, C., Dagli, C., Lentine, K., Schnitzler, M., Randall, H., Levanos, T., Rothweiler, R., Speir, L., Marklin, G. (2024). Investigation of Racial and Ethnic Bias in Kidney Non-Utilization Decisions Using the Deceased Donor Organ Allocation Model. American Journal of Transplantation, 24(6), s1. (extended abstract published from American Transplant Congress) [Blog post]
Ashiku, L., Threlkeld, R., Dzieran, R., Dagli, C., Canfield, C., Lentine, K., Randall, H., Schnitzler, M. (2024). AI-Model Interpretation for Deceased Donor Kidney Acceptance Practices. American Journal of Transplantation, 24(6), s1. (extended abstract published from American Transplant Congress)
Dzieran, R., Ashiku, L., Threlkeld, R., Dagli, C. & Marley, R. (2024). System-of-Systems Approach for Improving Quality of Kidney Transplant Decision-Making Support for Transplant Surgeons. The Proceedings of the 2024 Conference on Systems Engineering Research, 327-340. [Blog post]; https://doi.org/10.1007/978-3-031-62554-1
Telukunta, M., Rao, S., Stickney, G., Nadendla, V. S. S., & Canfield, C. (2024). Learning Social Fairness Preferences from Non-Expert Stakeholder Opinions in Kidney Placement. Conference on Health, Information and Learning (CHIL). [Blog post]; https://chilconference.org/2024/proceeding_P120.html; https://arxiv.org/pdf/2404.03800
Threlkeld, R., Ashiku, L., Dagli, C., Dzieran, R., Canfield, C., Lentine, K., Schnitzler, M., Marklin, G., Rothweiler, R., Speir, L., & Randall, H. (2023). AI-Enabled Digital Support to Increase Placement of Hard-to-Place Deceased Donor Kidneys. American Journal of Transplantation. (extended abstract published from American Transplant Congress)
Threlkeld, R., Ashiku, L., Dagli. C. (2023). A Use Case for Developing Meta Architectures with Artificial Intelligence and Agent Based Simulation in the Kidney Transplant Complex System of Systems. 18th Annual System of Systems Engineering Conference (SoSe), Lille, France, 2023. (published by the Institute of Electrical and Electronics Engineers (IEEE)).
Ashiku, L., Threlkeld, R., Dagli, C., Schnitzler, M., Canfield, C., Lentine, K., & Randall, H. (2022). Donor Disposition AI Model to Predict Transplant for Recovered Deceased Donor Kidneys. American Journal of Transplantation, 22(suppl 3), 652-653. (extended abstract published from American Transplant Congress)
Ashiku, L., Threlkeld, R., Canfield, C., & Dagli, C. (2022). Identifying AI Opportunities in Donor Kidney Acceptance: Incremental Hierarchical Systems Engineering Approach. IEEE Systems Conference (SysCon), pp. 1-8, doi: 10.1109/SysCon53536.2022.9773875.
R. Threlkeld, L. Ashiku, C. Dagli. (2022). Complex System Methodology for Meta Architecture optimization of the Kidney Transplant System of Systems. System of Systems Engineering Conference (SOSE), Rochester, NY. (published by IEEE (Institute of Electrical and Electronics Engineers)).
Ashiku, L., Al-Amin, Md., Madria, S., Dagli, C. (2021). Machine Learning Models and Big Data Tools for Evaluating Kidney Acceptance. Complex Adaptive Systems Conference, Big Data IoT and AI for a Smarter Future, Malvern, PA.
Schnitzler, M. A., Dagli, C., Canfield, C., Dzebisashvili, N., Varma, C., Axelrod, D., Lentine, K., Ouseph, R., & Randall, H. (2020). Using Artificial Intelligence Tools for Identification of High Risk Transplant Recipients for Focused Management. American Journal of Transplantation, 20(suppl 3), 283–284. (extended abstract published from American Transplant Congress)
Subramanian, H. V., Canfield, C., Shank, D. B., Andrews, L., & Dagli, C. (2020) Communicating Uncertain Information from Deep Learning Models in Human Machine Teams. Proceedings of the American Society for Engineering Management.
Presentations
2025. Dzieran, R., Dagli, C., Marley, R. An Adaptive Human-AI Teaming Framework for Complex Healthcare Decision Making: Capturing Transplant Surgeon Expertise Using Fuzzy Logic. Bioinnovation and Medical Engineering Symposium, Missouri University of Science and Technology, Rolla, MO. [Blog post]
2025. Fadaiya, O., Dagli, C. Dual-level Framework for Early Detection of Chronic Kidney Disease. Bioinnovation and Medical Engineering Symposium, Missouri University of Science and Technology, Rolla, MO. [Blog Post]
2025. Babaee A., Shank, D. B., Canfield, C., Hall, J. G. Tensions in AI Adoption for Organ Procurement Organizations. Bioinnovation and Medical Engineering Symposium, Missouri University of Science and Technology, Rolla, MO. [Blog post]
2025. Canfield, C. Designing Appropriate AI for Organ Allocation and Acceptance. The National Innovation Forum, The Alliance, Online. [Blog post]
2024. Canfield, C., Dagli, C., Shank, D. B., Nadendla, V. S. S., Subramanian, H. V., Telukunta, M., Dzieran, R., M., Lentine, K., Randall, H., Eberl, J., Miller, M., Cartwright, L., Cummiskey, B., Noreen, S., Ashiku, L., Threlkeld, R., Babaee, A., & Hall, J. G. AI Use in Kidney Allocation: Project Overview. Symposium on Bridging Disparities in Health Care Using Artificial Intelligence, Saint Louis University, Saint Louis, MO. [Blog post]
2024. Canfield, C., Dagli, C., Shank, D. B., Nadendla, V. S. S., Subramanian, H. V., Telukunta, M., Hall, J. G. Measuring and Aggregating Preferences for AI in Kidney Transplant Healthcare. The Artificial Intelligence and You: The Social and Human Dimensions of AI Symposium, Center for Science, Technology, and Society, Rolla, MO. [Blog post]
2024. Schnitzler, M., Dagli, C., Canfield, C., Caliskan, Y., Nandendla, V. S. S. Missouri S&T Center for Biomedical Research and Saint Louis University Biomedical and Health Informatics Symposium, Rolla, MO.
2024. Canfield, C., Dagli, C., Shank, D. B., Nadendla, V. S. S., Schnitzler, M., Lentine, K., Randall, H., Eberl, J., Miller, M., Cartwright, L., Cummiskey, B., Noreen, S., Ashiku, L., Threlkeld, R., Subramanian, H. V., Telukunta, M., Dzieran, R., Babaee, A., & Hall, J. G. Increasing Kidney Utilization Using Artificial Intelligence Decision Support. Association of Organ Procurement Organizations, San Antonio, TX.
2024. R. Threlkeld, L. Ashiku, C. Canfield, C. Dagli, K. Lentine, H. Randall, T. Levanos, R. Rothweiler, L. Speir, G. Marklin. Advanced AI Algorithms-Driven Agent Based Simulation for Policy Improvement in Hard-to-Place Deceased Donor Kidneys. 30th International Congress of The Transplantation Society.
2024. Babaee, A., Shank, D. B., & Canfield, C. What factors affect AI adoption by the public in the kidney transplant placement process? Society for Personality and Social Psychology (SPSP) Annual Convention, San Diego, CA.
2023. R. Dzieran, L. Ashiku, R. Threlkeld, C. Dagli, and R. Marley. Fuzzy Associative Memory and Deep Learning Network Model Interface with Transplant Surgeon in Assessing Hard-to-Place Kidneys for Use in Digital Twin Model. Council of Engineering Systems Universities (CESUN) 9th International Engineering Systems Symposium, Evanston, IL. *1st Place Poster Award Winner
2023. Subramanian, H. V. Drawing Parallels Between Domains to Design an AI Decision Support System. American Society for Engineering Management, Denver, CO.
2023. Telukunta, M., & Nadendla, V. S. S. Towards Inclusive Fairness Evaluation via Eliciting Disagreement Feedback from Non-Expert Stakeholders. BIAS Workshop at European Conference on Machine Learning (ECML/PKDD), Torino, Italy. https://arxiv.org/pdf/2304.03801
2023. Subramanian, H. V., Canfield, C., & Shank, D. B. Integrating Stakeholder Input into the Design of Explainable AI Interfaces: An Application in Kidney Transplant Healthcare. Institute of Industrial and Systems Engineers, New Orleans, LA.
2022. Subramanian, H. V., Canfield, C., Shank, D. B., & Dagli, C. The Role of Explainable AI in a Decision Support System for Kidney Transplant Placement. American Society for Engineering Management, Tampa, FL.
2021. Subramanian, H. V., Canfield, C., & Shank, D. B. Role of Uncertainty Information and Domain Knowledge in Use of Artificial Intelligence Recommendations. Society for Risk Analysis, Online.
2021. Subramanian, H. V., Canfield, C., Elder, H., Ashiku, L., Threlkeld, R., Hines, C., Dagli, C., Shank, D., Lentine, K., Schnitzler, M., & Randall, H. Engaging Stakeholders in the Transplant Community to Design Artificial Intelligence Decision Support. American Society for Engineering Management, Online.
2020. Subramanian. H. V., Canfield, C., Shank, D., Andrews, L., & Dagli, C. Designing Communications for AI Recommendations with Uncertain Truth. Society for Risk Analysis (SRA) Annual Meeting, Online.
2020. Elder, H., Canfield, C., Shank, D. B., & Hines, C. Can AI recommendations encourage riskier decision-making with higher reliability? Society for Risk Analysis (SRA) Annual Meeting, Online.
2019. Canfield, C., Shank, D. B., Andrews, L., & Dagli, C. Communicating Uncertainty in Deep Learning Models for High Stakes Decisions [Poster Platform]. Society for Risk Analysis (SRA) Annual Meeting, Arlington, VA.
Academic Works
Subramanian, H. V. (2025). Supporting Human-AI Interaction from User Expectations to Mental Models (Doctoral dissertation). Missouri University of Science and Technology.
Babaee, A. (2025). Sources of Tensions in AI Adoption for Organ Procurement Organizations (Master’s thesis). Missouri University of Science and Technology. Link
Telukunta, M. (2025) Topics on AU Fairness Preferences in Kidney Transplantation (Doctoral dissertation). Missouri University of Science and Technology. Link
Subramanian, H. V. (2020). Communicating Uncertain Information from Deep Learning Models to Users (Master’s thesis). Missouri University of Science and Technology. Link