在放射学中开发,购买,实施和监测AI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. adrianbrady@me.com.
Insights into imaging
|January 21, 2024
概括
放射学中的人工智能 (AI) 需要对安全性和实用性进行仔细评估. 开发人员,监管机构和临床医生之间的合作对于道德的人工智能集成和改善患者护理至关重要.
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.
- 人工智能工具的日益普及需要对其临床实用性和安全性进行批判性评估.
- 国际放射学协会强调,需要采取统一的方法来整合人工智能.
研究的目的:
- 定义与放射学中的AI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临床AI实施之前考虑.
- 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,介绍了来自北美,欧洲,澳大利亚和新西兰的观点.
- 确定人工智能开发和临床整合的关键问题.
- 关于人工智能性能和安全的监测策略的建议.
主要成果:
- 人工智能在放射学中的整合需要加强对实用性和安全性的监测.
- 利益相关者之间的合作对于解决伦理问题和绩效至关重要.
- 从开发到临床集成,严格的评估是人工智能使患者受益的关键.
结论:
- 人工智能对放射学具有变革性的潜力,可以改善诊断和患者管理.
- 积极解决实际和道德问题对于负责任的AI采用至关重要.
- 持续的监测和协作确保AI在医疗保健中的安全和有效使用.
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