Reducing Kidney Discard With Artificial Intelligence Decision Support: the Need for a Transdisciplinary Systems Approach

Richard Threlkeld, Lirim Ashiku, Casey Canfield, Daniel B. Shank, Mark A. Schnitzler, Krista L. Lentine, David A. Axelrod, Anil Choudary Reddy Battineni, Henry Randall, Cihan Dagli

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations


Purpose of Review: A transdisciplinary systems approach to the design of an artificial intelligence (AI) decision support system can more effectively address the limitations of AI systems. By incorporating stakeholder input early in the process, the final product is more likely to improve decision-making and effectively reduce kidney discard. Recent Findings: Kidney discard is a complex problem that will require increased coordination between transplant stakeholders. An AI decision support system has significant potential, but there are challenges associated with overfitting, poor explainability, and inadequate trust. A transdisciplinary approach provides a holistic perspective that incorporates expertise from engineering, social science, and transplant healthcare. A systems approach leverages techniques for visualizing the system architecture to support solution design from multiple perspectives. Summary: Developing a systems-based approach to AI decision support involves engaging in a cycle of documenting the system architecture, identifying pain points, developing prototypes, and validating the system. Early efforts have focused on describing process issues to prioritize tasks that would benefit from AI support.

Original languageEnglish (US)
Pages (from-to)263-271
Number of pages9
JournalCurrent Transplantation Reports
Issue number4
StatePublished - Dec 2021


  • Artificial intelligence
  • Decision-making
  • Kidney discard
  • Systems science
  • Transdisciplinary

ASJC Scopus subject areas

  • Surgery
  • Immunology
  • Hepatology
  • Nephrology
  • Transplantation


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