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Trustworthy AI Tools for the Prediction of Obesity Related Vascular Diseases (AI-POD)

Trustworthy AI Tools for the Prediction of Obesity Related Vascular Diseases (AI-POD)
用于预测肥胖相关血管疾病的值得信赖的人工智能工具 (AI-POD)
批准号:
10064113
负责人:
金额:
$70.15万
依托单位:
依托单位国家:
英国
项目类别:
EU-Funded
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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英文摘要
Weight problems and obesity are increasing at a rapid rate already concerning more than 436mio people in European countries. Obese persons have a 50% higher risk of cardio-vascular disease (CVD) mortality and treatment costs result in a total economic burden of over 210 billion Euro per year. To date the prediction of the individual risk for major adverse CVD events in the obese patient population is a challenge. Current risk scores are not sufficiently accurate and there is no implementation of scores into user friendly solutions. The AI-POD project aims to reduce the number of CVD related deaths in Europe by developing an AI-based risk prediction score to support clinical decision making and by equipping obese persons with trustworthy AI tools. AI tools will integrate clinical, laboratory and imaging data to translate disease risk into actionable health information to guide diagnostic steps and treatment recommendations. The tools will be validated in six clinical sites on CVD and serve as the basis for a lasting interdisciplinary platform for distributed learning in other vascular territories. AI-POD will push the boundaries of clinical insight in CVD in obese persons, including its treatment and risk management. AI-POD main outcomes are (1) a novel imaging-based AI-based risk score and Clinical Decision Support System (CDSS) for the risk assessment and prediction of obesity-related CVD and associated complications as a pre-requiste for further AIbased prevention and treatment management; (2) an innovative, easy-to-use mobile app for citizens (Citizen App) that interacts with the CDSS empowering obese people to better monitor and manage their own health. Physicians will benefit from more efficient workflows and in consequence, public health budgets will be unburdened by reducing morbidity and mortality of obese indiviudals.
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