在放射学中开发,采购,实施和监测人工智能工具:实际考虑. 来自ACR,CAR,ESR,RANZCR和RSNA的多社会声明
Adrian P Brady1, Bibb Allen2,3, Jaron Chong4
1University College Cork, Cork, Ireland.
概括
放射学中的人工智能 (AI) 提供了变革性的潜力,但需要仔细评估. 本文讨论了在临床实践中安全整合人工智能的实际和伦理问题.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 为放射学带来了重大机遇和挑战.
- 越来越多的人工智能工具的可用性需要对它们的实用性和安全性进行批判性评估.
- 现有的文献缺乏对放射学中人工智能的实用和伦理考虑的全面概述.
研究的目的:
- 在放射学实践中定义围绕AI整合的实际问题和伦理问题.
- 为开发人员,监管机构和人工智能工具购买者提供指导.
- 建议监测人工智能稳定性,安全性和适合自主功能的方法.
主要方法:
- 多社团立场陈述综合了国际放射学学会的观点.
- 审查与人工智能实施相关的潜在实际挑战和道德困境.
- 为人工智能工具开发,监管和临床使用制定建议.
主要成果:
- 确定了关于人工智能的实用性,安全性和放射学中的伦理影响的关键问题.
- 概述了人工智能工具开发人员,监管机构和购买者需要考虑的关键因素.
- 建议在临床环境中持续监测AI性能和安全的策略.
结论:
- 仔细考虑实际和伦理问题对于成功将AI整合到放射学中至关重要.
- 涉及所有利益相关者的协作方法对于负责任的AI开发和实施至关重要.
- 建立强大的监测机制将确保AI工具在临床实践中安全有效地使用.
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