4 papers
A Latent ODE Approach to Spatiotemporal Modeling of Cine Cardiac MRI
David Brüggemann, Ekaterina Krymova, Firat Ãzdemir +6
Cardiac magnetic resonance imaging (CMR) captures rich spatiotemporal information about ventricular structure and motion, but conventional risk models use only a few image-derived…
Advancing Stroke Risk Prediction Using a Multi-modal Foundation Model
Camille Delgrange, Olga Demler, Samia Mora +3
Predicting stroke risk is a complex challenge that can be enhanced by integrating diverse clinically available data modalities. This study introduces a self-supervised multimodal f…
Enhancing Cardiovascular Disease Prediction through Multi-Modal Self-Supervised Learning
Francesco Girlanda, Olga Demler, Bjoern Menze +1
Accurate prediction of cardiovascular diseases remains imperative for early diagnosis and intervention, necessitating robust and precise predictive models. Recently, there has been…
Predicting Stroke through Retinal Graphs and Multimodal Self-supervised Learning
Yuqing Huang, Bastian Wittmann, Olga Demler +2
Early identification of stroke is crucial for intervention, requiring reliable models. We proposed an efficient retinal image representation together with clinical information to c…