У нас вы можете посмотреть бесплатно AI-POD Project Webinar on AI for Cardiovascular Risk & Prevention или скачать в максимальном доступном качестве, видео которое было загружено на ютуб. Для загрузки выберите вариант из формы ниже:
Если кнопки скачивания не
загрузились
НАЖМИТЕ ЗДЕСЬ или обновите страницу
Если возникают проблемы со скачиванием видео, пожалуйста напишите в поддержку по адресу внизу
страницы.
Спасибо за использование сервиса ClipSaver.ru
ESR-EIBIR Webinar Series: Exploring AI for Clinical Decision-Making AI for Cardiovascular Risk & Prevention. Programme: 09:00 – 09:05 | Welcome – Regina Beets-Tan, The Netherlands Cancer Institute, Netherlands 09:05 – 09:10 | Trustworthy AI for a Healthier Future: The AI-POD Project – A. Bartashova, Medical University of Vienna, Austria 09:10 – 09:25 | Behind the Score: Developing the AI-POD Risk Prediction – G. Langs, University of Vienna, Austria 09:25 – 09:40 | Building Smarter Tools: AI-POD Clinical Decision Support System (CDSS) – J. Kirchhoff, medicalvalues GmbH, Germany 09:40 – 09:50 | The AI-POD Citizen App: Features and Functionalities – F. Catarinella, Brightfish B.V, Netherlands. 09:50 – 10:05 | From Prediction to Prevention: How AI-POD Supports Better Vascular Risk Management – S. Al-Basri, BG University Hospital Bergmannsheil Bochum, Germany 10:05 – 10:15 | Human-Centred AI: A Stakeholder Perspective on AI for Imaging-Based Prediction of Obesity-Related Vascular Diseases – E. Van Steijvoort, Katholieke Universiteit Leuven, Belgium 10:15 – 10:30 | Panel Discussion: Integrating AI-POD into the Clinical Workflow: Opportunities and Challenges – R. Beets Tan, The Netherlands Cancer Institute, Netherlands The AI-POD project, funded by the Horizon Europe funding programme, aims to have significant impacts at multiple levels, expecting to revolutionize obesity and CVD management through AI-based clinical Decision Support System and Citizen App. For more information on the project, please visit the AI-POD website: https://ai-pod.eu/ 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.