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
R. Dzieran, R. Threlkeld, L. Ashiku, C. Canfield, C. Dagli, R. J. Marley, K. Lentine, H. Randall, M. Schnitzler, T. Levanos, R. Rothweiler, L. Speir, and G. Marklin. (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
R. Threlkeld, L. Ashiku, R. Dzieran, M. Sandeep, C. Canfield, C. Dagli, K. Lentine, M. Schnitzler, H. Randall, T. Levanos, R. Rothweiler, L. Speir, G. Marklin. (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)
L. Ashiku, R. Threlkeld, R. Dzieran, C. Dagli, C. Canfield, K. Lentine, H. Randall, M. Schnitzler. (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.
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). 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)
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.
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
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, 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.