DEVELOPING TRUSTWORTHY ARTIFICIAL INTELLIGENCE (AI)- DRIVEN TOOLS TO PREDICT VASCULAR DISEASE RISK AND PROGRESSION - VASCULAID

vascular - aid的目的是预测心血管事件的风险和血管疾病腹主动脉瘤（AAA）和外周动脉疾病（PAD）的进展，以影响疾病的进程，改善患者的生活质量和护理，并帮助临床医生做出更明智的涉及患者的决策。vascular - aid将使我们首次能够识别AAA级生长或PAD进展和心血管事件高风险的患者。为此，我们将提供一个与临床相关且具有成本效益且值得信赖的人工智能驱动平台（vascull - aid），该平台整合了多源参数，包括成像、蛋白质组学和基因组数据，以及来自可穿戴设备的患者生活方式数据，从而实现个性化血管疾病管理。为了最大限度地提高个性化的预防策略，vascular - aid利用可视化工具来改善临床与患者的沟通，并赋予患者权力。vascull - aid平台由人工智能风险预测工具、患者沟通应用程序和临床仪表板组成，以支持临床决策。特别强调道德，以确保人工智能预测工具的有益实施。在这个项目中，我们的目标是(1)建立一个欧盟范围内的数据基础设施，(2)开发一个基于人工智能的AAA和PAD进展预测工具，(3)根据COMET计划制定标准来评估vascular - aid的有效性，(4)对vascular - aid平台进行临床测试和概念验证。一旦得到验证，该平台也可以扩展到其他心血管疾病（cvd）。vascull - aid汇集了14个领先的组织（和2个附属实体），包括临床学术中心、研究所、大学和中小企业，以及覆盖整个价值链的大型行业、患者组织和政策制定者，以实现将平台整合到临床实践中。

The aim of VASCUL-AID is to predict the risk of cardiovascular events and progression of the vascular diseases Abdominal Aortic Aneurysm (AAA) and Peripheral Arterial Disease (PAD) to influence the course of disease improving the patient’s quality of life and care and assisting clinicians to make better-informed decisions involving the patient. VASCUL-AID will allow us for the first time to identify patients who are at high risk for AAA growth or PAD progression and cardiovascular events. To this end, we will deliver a clinically relevant and cost-effective trustworthy AI-driven platform (VASCUL-AID) that integrates multi-source parameters including imaging, proteomic and genomic data as well as life-style patient data from wearables to enable personalised vascular disease management. To maximise the personalised prevention strategies, VASCUL-AID leverages visualisation toolsto improve clinician-patient communication and empower the patient. The VASCUL-AID platform consists of AI risk-prediction tools, a patient communication app an a clinical dashboard to support clinical decision-making. A particular emphasis is placed on ethics, to ensure beneficial implementation of AI prediction tools. In this project, we aim to (1) build an EU-wide data infrastructure, (2) develop an AI-based progression prediction tools for AAA and PAD, (3) develop criteria according to the COMET initiative to assess the effectiveness of VASCUL-AID, and (4) clinically test and show proof-of-concept for the VASCUL-AID platform. Once validated, this platform can be extended to other cardiovascular diseases(CVDs) as well. VASCUL-AID bringstogether 14 leading organisations(and 2 affiliated entities) consisting of clinical academic centres, institutes, universities and SMEs as well as large industry, patients organisations and policy makers that cover the full value chain to enable integration of the platform into clinical practice.