Reducing Kidney Discard With Artificial Intelligence Decision Support: the Need for a Transdisciplinary Systems Approach.
Reducing Kidney Discard With Artificial Intelligence Decision Support: the Need for a Transdisciplinary Systems Approach.
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DOI：
10.1007/s40472-021-00351-0
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发表时间：
2021
影响因子：
2.1
通讯作者：
Dagli C
中科院分区：
文献类型：
--
作者：
Threlkeld R;Ashiku L;Canfield C;Shank DB;Schnitzler MA;Lentine KL;Axelrod DA;Battineni ACR;Randall H;Dagli C
一个跨学科的系统方法来设计的人工智能（AI）决策支持系统可以更有效地解决人工智能系统的局限性。通过在过程的早期纳入利益相关者的意见，最终产品更有可能改善决策并有效减少肾脏丢弃。肾脏丢弃是一个复杂的问题，需要移植利益相关者之间加强协调。人工智能决策支持系统具有巨大的潜力，但也存在与过度拟合、可解释性差和信任不足相关的挑战。跨学科的方法提供了一个整体的视角，结合了工程，社会科学和移植医疗保健的专业知识。系统方法利用可视化系统架构的技术，从多个角度支持解决方案设计。开发基于系统的人工智能决策支持方法涉及记录系统架构、识别痛点、开发原型和验证系统的循环。早期的努力集中在描述流程问题，以优先考虑将受益于AI支持的任务。
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.
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影响因子：
8.8
作者：
Hart, A.;Lentine, K. L.;Snyder, J. J.
通讯作者：
Snyder, J. J.
影响因子：
2
作者：
Miller, Michael E.;McGuirl, John M.;Ford, Thomas C.
通讯作者：
Ford, Thomas C.
影响因子：
5.4
作者：
Dietvorst, Berkeley J.;Simmons, Joseph P.;Massey, Cade
通讯作者：
Massey, Cade
影响因子：
56.9
作者：
DAWES, RM;FAUST, D;MEEHL, PE
通讯作者：
MEEHL, PE
DOI：
10.7861/futurehosp.5-3-151
发表时间：
2018-10-01
期刊：
Future healthcare journal
影响因子：
--
作者：
Clarkson, John;Dean, John;Bashford, Tom
通讯作者：
Bashford, Tom