Developing a medical imaging AI development and evaluation platform
Developing a medical imaging AI development and evaluation platform
批准号:
10067155
负责人:
金额:
$6.36万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2023
资助国家:
英国
项目状态:
已结题
起止时间:
2023 至 --
中文摘要
人工智能工具已经显示出能够评估医学成像并帮助医疗保健专业人员进行图像解释的速度和准确性。然而,由于多种原因,医疗机构对这些算法的采用一直很缓慢。其中最主要的是对算法的性能缺乏信任。在做出购买决定之前,临床医生希望尝试算法来测试其可用性和准确性。这需要将算法与实时临床IT系统集成,这需要医院的技术和信息治理团队的输入,并且是实施的主要障碍。此外,购买后,工作人员需要接受如何使用算法的培训。该项目旨在通过加速采用人工智能(AI)进行医学图像解释来改善NHS诊断途径。为此,RAIQC Ltd旨在开发一个基于云的平台,作为培训,测试和部署AI算法的端到端解决方案。使用该平台,AI开发人员将能够执行_insilico_临床试验,以生成有关其AI工具的有效性,可用性和健康经济价值的证据。该平台还将允许医疗服务提供商在将算法部署到临床实践之前对其进行试验,并能够培训其员工安全使用这些工具。在项目的第一阶段,RAIQC Ltd将汇集商业AI开发人员,学术组织和医疗成像AI的最终用户(如医院和医疗保健专业人员)。该小组将能够概述每个利益相关者在开发和将医学成像AI转化为临床实践方面的需求。RAIQC Ltd还将与利益相关者合作,定义AI开发和部署路径每个阶段的技术要求。
英文摘要
AI tools have shown promise in being able to evaluate medical imaging and aid healthcare professionals with their image interpretation speed and accuracy. However, the uptake of these algorithms by healthcare organisations has been slow for a number of reasons. Primary among this has been a lack of trust in the performance of algorithms. Before making a purchase decision, clinicians want to try algorithms to test their usability and accuracy. This requires integrating algorithms with live clinical IT systems which needs input from technical and information governance teams at the hospitals and is a major barrier to implementation. Moreover, after purchase, there is a requirement for staff to be trained in how touse the algorithms.The project aims to improve NHS diagnostic pathways by accelerating adoption of artificial intelligence (AI) for medical image interpretation. To do this, RAIQC Ltd aims to develop a cloud-based platform that acts as an an end-to-end solution for training, testing and deploying AI algorithms.Using this platform, AI developers will be able to perform _insilico_ clinical trials to generate evidence around the efficacy, usability and health economic value of their AI tools. The platform will also allow healthcare providers to trial algorithms prior to deploying them into clinical practice as well as being able to train their staff in safe use of these tools.During phase 1 of the project, RAIQC Ltd will bring together a consortium of commercial AI developers, academic organisations and end users of medical imaging AI such as hospitals and healthcare professionals. The group will be able to outline needs of each stakeholder in the development and translation of medical imaging AI into clinical practice. RAIQC Ltd will also work with the stakeholders to define the technical requirements for each stage of the AI development and deployment pathway.
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