1 citations · 1 across the 3 of their papers we have counts for
3 papers
NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting
Tobias Susetzky, Raphael Rehms, Dmitrii Seletkov +5
The digitization of healthcare has generated vast, longitudinal, and multimodal patient records over a lifetime, yet fully exploiting these data to represent and predict patient st…
Calibrated Confidence Expression for Radiology Report Generation
David Bani-Harouni, Chantal Pellegrini, Julian Lüers +6
Safe deployment of Large Vision-Language Models (LVLMs) in radiology report generation requires not only accurate predictions but also clinically interpretable indicators of when o…
Survival In-Context: Amortized Bayesian Survival Analysis via Prior-Fitted Networks
Dmitrii Seletkov, Paul Hager, Georgios Kaissis +3
Survival analysis is crucial for many medical applications, but remains challenging for modern machine learning due to limited data, censoring, and the heterogeneity of tabular cov…