7 papers
LiD-GLM: Lipschitz-constrained Deep Generalized Linear Models
Tom Splittgerber, Niklas Koenen, Marvin N. Wright +1
The combination of traditional statistical models and neural network (NN) components into semi-structured hybrid models is an intriguing approach to construct models that, ideally,…
xMICD: Explainable Representation of Multiple ICD Codes
Pat Vatiwutipong, Kumkup Keeratisiwakul, Albert Phuoc Kien Van Truong +4
Electronic Health Records (EHRs) are widely used for clinical risk prediction using machine learning. International Classification of Diseases (ICD) codes provide structured inform…
Multimodal synthesis of MRI and tabular data with diffusion in a joint latent space via cross-attention
Daniel Mensing, Jan Kapar, Jochen G. Hirsch +3
We propose a multimodal latent diffusion model that jointly synthesizes volumetric magnetic resonance imaging (MRI) and tabular clinical data within a shared latent space via cross…
Functional Decomposition and Shapley Interactions for Interpreting Survival Models
Sophie Hanna Langbein, Hubert Baniecki, Fabian Fumagalli +3
Hazard and survival functions are natural, interpretable targets in time-to-event prediction, but their inherent non-additivity fundamentally limits standard additive explanation m…
Machine Learning in Epidemiology
Marvin N. Wright, Lukas Burk, Pegah Golchian +3
In the age of digital epidemiology, epidemiologists are faced by an increasing amount of data of growing complexity and dimensionality. Machine learning is a set of powerful tools…
GRANITE: A Generalized Regional Framework for Identifying Agreement in Feature-Based Explanations
Julia Herbinger, Gabriel Laberge, Maximilian Muschalik +3
Feature-based explanation methods aim to quantify how features influence the model's behavior, either locally or globally, but different methods often disagree, producing conflicti…