The AI4HF consortium has released a new episode of its podcast as part of the Cardio Talk: Latest Research series.
In this episode, Professors Pim van der Harst and Folkert Asselbergs, together with Assistant Professor Jessica van Setten, discuss how federated learning enables researchers to generate synthetic, fully anonymous cardiology data across sites. This approach helps overcome the lack of multimodal datasets in the public domain and allows scientists worldwide to develop new algorithms for cardiovascular disease.
For patients, this means that AI-based models can be trained on richer, more representative data, advancing early detection, more accurate prediction, and better treatment of heart failure, all while safeguarding privacy.
The episode is available on ESC 365, Spotify, Apple Podcasts, and other platforms.
Click here to listen to the AI4HF podcast
The AI4HF (Artificial Intelligence for Heart Failure) project aims to harness the power of artificial intelligence to improve the prediction, prevention, and management of heart failure through the use of large-scale clinical data.
Click here to learn more about the AI4HF project