2 citations · 2 across the 4 of their papers we have counts for
5 papers
Large language models as synthetic clinical experts to inform longitudinal rare-disease modeling
Clemens Schächter, Astrid Pechmann, Janbernd Kirschner +2
Due to the limited amount of information, modeling longitudinal rare-disease data can benefit from integrating clinical knowledge. Yet, elicitation of expert knowledge and formaliz…
Using latent representations to link disjoint longitudinal data for mixed-effects regression
Clemens Schächter, Maren Hackenberg, Michelle Pfaffenlehner +6
Many rare diseases offer limited established treatment options, leading patients to switch therapies when new medications emerge. To analyze the impact of such treatment switches w…
Investigating a domain adaptation approach for integrating different measurement instruments in a longitudinal clinical registry
Maren Hackenberg, Michelle Pfaffenlehner, Max Behrens +3
In a longitudinal clinical registry, different measurement instruments might have been used for assessing individuals at different time points. To combine them, we investigate deep…
A statistical approach to latent dynamic modeling with differential equations
Maren Hackenberg, Astrid Pechmann, Clemens Kreutz +2
Ordinary differential equations (ODEs) can provide mechanistic models of temporally local changes of processes, where parameters are often informed by external knowledge. While ODE…
Deep dynamic modeling with just two time points: Can we still allow for individual trajectories?
Maren Hackenberg, Philipp Harms, Michelle Pfaffenlehner +4
Longitudinal biomedical data are often characterized by a sparse time grid and individual-specific development patterns. Specifically, in epidemiological cohort studies and clinica…