AI Trust Audit - A novel solution and process to advance trust in the compliance and risk of AI systems in radiology
AI 信任审计 - 一种新颖的解决方案和流程,可提高放射学中 AI 系统合规性和风险的信任
基本信息
- 批准号:10076466
- 负责人:
- 金额:$ 6.37万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Grant for R&D
- 财政年份:2023
- 资助国家:英国
- 起止时间:2023 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Radiology AI products have the potential to revolutionise the healthcare industry by improving patient outcomes, reducing errors, and increasing efficiency. However, the adoption of these products has been slow due to concerns over their reliability, robustness, and compliance. The lack of transparency in the development and testing of AI systems has raised questions about their safety and effectiveness.The AI Trust Audit project aims to develop a novel solution to advance trust in the compliance and risk of AI systems auditing, impact assessment, or evaluation, reliability and robustness testing of radiology AI products. This project is essential as radiology AI products are becoming more widely used, and there is a growing need to ensure that they are reliable, trustworthy and have a positive impact on patients and healthcare providers.The proposed solution will be a software-based AI Trust Audit tool, which will use machine learning algorithms to assess the compliance, risk, and reliability of radiology AI products. The tool will perform automated testing and auditing, as well as impact and risk assessments, to identify potential issues with reliability of these products. The tool will be designed to integrate seamlessly with existing radiology workflows and software systems, making it easy for healthcare providers to use and adopt.The impact of this project will be significant for patients, healthcare providers, and the wider healthcare industry. The AI Trust Audit tool will improve patient safety by identifying and addressing potential issues with radiology AI products before they cause harm. It will also provide healthcare providers with greater confidence in the reliability and performance of these products, leading to increased adoption and improved patient outcomes.In addition to the positive impact on patient outcomes, this project will also benefit the UK economy by supporting the development of a new and innovative healthcare technology. Overall, the AI Trust Audit project is a crucial step forward in ensuring the safe and effective use of radiology AI products. By developing a comprehensive and automated tool that addresses the unique challenges and risks of these products, this project has the potential to revolutionise the way radiology AI products are tested, evaluated, and audited.
放射学AI产品有可能通过改善患者预后、减少错误和提高效率来彻底改变医疗保健行业。然而,由于对其可靠性、鲁棒性和合规性的担忧,这些产品的采用一直很缓慢。人工智能系统的开发和测试缺乏透明度,引发了人们对其安全性和有效性的质疑。人工智能信任审计项目旨在开发一种新的解决方案,以提高对人工智能系统审计、影响评估或评估的合规性和风险的信任,以及放射学人工智能产品的可靠性和鲁棒性测试。随着放射学人工智能产品的应用越来越广泛,人们越来越需要确保其可靠、值得信赖并对患者和医疗服务提供者产生积极影响,该项目至关重要。拟议的解决方案将是一个基于软件的人工智能信任审计工具,该工具将使用机器学习算法来评估放射学人工智能产品的合规性、风险和可靠性。该工具将进行自动化测试和审计,以及影响和风险评估,以确定这些产品可靠性的潜在问题。该工具将设计为与现有的放射学工作流程和软件系统无缝集成,使医疗保健提供者易于使用和采用。该项目对患者、医疗保健提供者和更广泛的医疗保健行业将产生重大影响。AI信任审计工具将通过在放射学AI产品造成伤害之前识别和解决潜在问题来提高患者安全性。它还将为医疗保健提供者提供更大的信心,这些产品的可靠性和性能,导致增加采用和改善患者的结果。除了对患者的结果产生积极影响,该项目还将通过支持新的创新医疗保健技术的发展,使英国经济受益。总的来说,人工智能信任审计项目是确保放射学人工智能产品安全有效使用的关键一步。通过开发一个全面的自动化工具来解决这些产品的独特挑战和风险,该项目有可能彻底改变放射学AI产品的测试,评估和审核方式。
项目成果
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其他文献
吉治仁志 他: "トランスジェニックマウスによるTIMP-1の線維化促進機序"最新医学. 55. 1781-1787 (2000)
Hitoshi Yoshiji 等:“转基因小鼠中 TIMP-1 的促纤维化机制”现代医学 55. 1781-1787 (2000)。
- DOI:
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LiDAR Implementations for Autonomous Vehicle Applications
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
吉治仁志 他: "イラスト医学&サイエンスシリーズ血管の分子医学"羊土社(渋谷正史編). 125 (2000)
Hitoshi Yoshiji 等人:“血管医学与科学系列分子医学图解”Yodosha(涉谷正志编辑)125(2000)。
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Effect of manidipine hydrochloride,a calcium antagonist,on isoproterenol-induced left ventricular hypertrophy: "Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,K.,Teragaki,M.,Iwao,H.and Yoshikawa,J." Jpn Circ J. 62(1). 47-52 (1998)
钙拮抗剂盐酸马尼地平对异丙肾上腺素引起的左心室肥厚的影响:“Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,
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