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, Jaron Chong3
1University College Cork, Cork, Ireland.
Journal of the American College of Radiology : JACR
|January 26, 2024
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. 本文讨论了在放射学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) 为推进放射学诊断,量化和管理提供了重大机会.
- 越来越多的人工智能工具的可用性需要进行批判性评估,以区分有益的应用程序和可能有害的应用程序.
研究的目的:
- 定义与将AI整合到放射学实践中相关的实际问题和伦理问题.
- 引导开发人员,监管机构和购买者在AI实施之前考虑关键问题.
- 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:
- 一个多社会论文,介绍了国际放射学学会 (美国,加拿大,欧洲,澳大利亚,新西兰) 的观点.
- 在临床放射学中对人工智能的实践和伦理问题的概述.
- 关于临床使用人工智能工具的监测策略的建议.
主要成果:
- 确定了围绕放射学AI的潜在实际问题和伦理问题.
- 概述了人工智能工具开发人员,监管机构和采购者的关键考虑因素.
- 建议监测人工智能性能,安全和自主能力的方法.
结论:
- 对人工智能的实用性和安全性的批判性评估对于负责任地融入放射学至关重要.
- 涉及所有利益相关者的协作方法对于AI在放射实践中的成功开发和实施至关重要.
- 持续监测至关重要,以确保人工智能工具的稳定性,安全性和适合临床使用.
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