The AI-POD consortium has officially launched the second edition of its project newsletter, offering a comprehensive update on its ongoing mission to revolutionise obesity-related disease prediction for cardiovascular conditions. This
The AI-POD project is inviting individuals and healthcare professionals to participate in a short online survey exploring the use of AI tools to predict obesity-related cardiovascular diseases. As part of
The AI-POD consortium convened in Vienna for its third in-person meeting, bringing together partners from across Europe to review progress, share insights, and align on upcoming priorities. Hosted by the
The AI-POD Project is gearing up for an exciting and important milestone as it prepares for its upcoming consortium meeting in Vienna. The event will bring together key project partners
AI-POD project was featured at the European Congress of Radiology (ECR) 2025, showcasing the transformative potential of AI in clinical decision-making. The project was presented as part of the session
The AI-POD Project aims to develop trustworthy AI tools to predict the risk of cardiovascular diseases in individuals living with obesity. To ensure the responsible development of these tools, we
The groundbreaking project AI-POD will be showcased at the European Congress of Radiology (ECR) 2025 in the session titled “Intelligence at Work: Harnessing Artificial Intelligence (AI) for Clinical Decision-Making.” This
On October 10th, 2024, the project team held a pivotal meeting with the External Advisory Board (EAB) to present several important updates and foster collaborative discussions on the project’s ongoing
Ulrike Attenberger took up the Professorship of Radiology (§98) at the Medical University of Vienna on July 15, 2024. At the same time, she took over as Head of the
The AI-POD clinical study has reached a significant milestone as three institutions have successfully enrolled their first patients. The Faculty of Medicine at Charles University in Pilsen, Ruprecht-Karls-Universität Heidelberg, Medical
AI-POD has been announced that our project has been highlighted on the European Society of Radiology’s Patients Page. This recognition is a significant milestone for our team, dedicated to revolutionising
At the AI-POD Project, we are on a mission to revolutionise the way we approach cardiovascular disease (CVD) prevention. Over the past year, our team of dedicated researchers and clinicians
On April 24th, the 1st Stakeholder and End-user webinar was held to introduce the AI-POD project, gather feedback, and facilitate collaboration among clinicians, researchers, patients/citizens, policy- and decision-makers, and obesity-related
AI-POD is a transformative initiative set out to revolutionise obesity-related disease prediction for cardiovascular disease. The mission of AI-POD is to significantly improve the risk assessment and management of obesity-related
AI-POD was featured at the European Congress of Radiology 2024 (28 February – 3 March 2024, Vienna). The open-access EIBIR session on Trustworthy AI tools for the prediction of obesity-related
On 27 February 2024, the AI-POD consortium and External Advisory Board convened at the Austria Centre Vienna for their annual consortium meeting, which was held as a hybrid session. The
AI-POD will be featured at the European Congress of Radiology 2024. AI-POD Coordinator Ulrike Attenberger and WP3 Lead Georg Langs will speak on “AI-POD: trustworthy AI tools for the prediction
AI-POD is excited to share a new project video highlighting our project’s objective to transform cardiovascular health. This video introduces our innovative AI-based risk score, designed to predict and prevent
May 22, 2023 – A groundbreaking EU-funded project, AI-POD, has been launched by a consortium of 11 partners from eight countries, with the ambitious goal of reducing cardiovascular disease (CVD)
AI-POD is a pioneering initiative that leverages Artificial Intelligence to combat obesity-related cardiovascular diseases, offering personalized treatment solutions and aiming to revolutionize healthcare by enhancing efficiency, patient autonomy, and cost-effectiveness.
This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement 101080302, and from the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number 23.00174.
Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union, the European Health and Digital Executive Agency (HADEA) or the Swiss State Secretariat for Education, Research and Innovation (SERI). Neither the European Union, SERI nor the granting authority can be held responsible for them.