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

doi:10.1007/s40472-021-00351-0

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

Journal article

Open access

Peer reviewed

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 and Cihan Dagli

Current transplantation reports, Vol.8(4), pp.263-271

2021

DOI: 10.1007/s40472-021-00351-0

PMCID: PMC8727423

PMID: 35059280

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https://doi.org/10.1007/s40472-021-00351-0View

Published (Version of record) Open Access

Abstract

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. 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. 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.

Decision-making

Systems science

Transdisciplinary

Artificial intelligence

Kidney discard

Details

Title: Subtitle: Reducing Kidney Discard With Artificial Intelligence Decision Support: the Need for a Transdisciplinary Systems Approach
Creators: Richard Threlkeld - Missouri University of Science and Technology
Lirim Ashiku - Missouri University of Science and Technology
Casey Canfield - Missouri University of Science and Technology
Daniel B Shank - Missouri University of Science and Technology
Mark A Schnitzler - Saint Louis University
Krista L Lentine - Saint Louis University
David A Axelrod - University of Iowa
Anil Choudary Reddy Battineni - Saint Louis University
Henry Randall - Saint Louis University
Cihan Dagli - Missouri University of Science and Technology
Resource Type: Journal article
Publication Details: Current transplantation reports, Vol.8(4), pp.263-271
DOI: 10.1007/s40472-021-00351-0
PMID: 35059280
PMCID: PMC8727423
NLM abbreviation: Curr Transplant Rep
ISSN: 2196-3029
eISSN: 2196-3029
Grant note: R01 DK102981 / NIDDK NIH HHS
Language: English
Date published: 2021
Academic Unit: Surgery
Record Identifier: 9984322953602771

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