40 citations · 42 across the 9 of their papers we have counts for
9 papers
Contrastive Representation Learning of Longitudinal Disease Trajectories on Temporal Graphs
Bastian Pfeifer
Understanding disease trajectories from longitudinal clinical data remains challenging due to complex temporal dynamics and heterogeneous patient cohorts. Here, we present a contra…
Feature graphs for interpretable unsupervised tree ensembles: centrality, interaction, and application in disease subtyping
Christel Sirocchi, Martin Urschler, Bastian Pfeifer
Interpretable machine learning has emerged as central in leveraging artificial intelligence within high-stakes domains such as healthcare, where understanding the rationale behind…
Federated unsupervised random forest for privacy-preserving patient stratification
Bastian Pfeifer, Christel Sirocchi, Marcus D. Bloice +2
In the realm of precision medicine, effective patient stratification and disease subtyping demand innovative methodologies tailored for multi-omics data. Clustering techniques appl…
Be Careful When Evaluating Explanations Regarding Ground Truth
Hubert Baniecki, Maciej Chrabaszcz, Andreas Holzinger +3
Evaluating explanations of image classifiers regarding ground truth, e.g. segmentation masks defined by human perception, primarily evaluates the quality of the models under consid…
Explaining and visualizing black-box models through counterfactual paths
Bastian Pfeifer, Mateusz Krzyzinski, Hubert Baniecki +3
Explainable AI (XAI) is an increasingly important area of machine learning research, which aims to make black-box models transparent and interpretable. In this paper, we propose a…
Bayesian post-hoc regularization of random forests
Bastian Pfeifer
Random Forests are powerful ensemble learning algorithms widely used in various machine learning tasks. However, they have a tendency to overfit noisy or irrelevant features, which…
Parea: multi-view ensemble clustering for cancer subtype discovery
Bastian Pfeifer, Marcus D. Bloice, Michael G. Schimek
Multi-view clustering methods are essential for the stratification of patients into sub-groups of similar molecular characteristics. In recent years, a wide range of methods has be…
Secondary Use of Clinical Problem List Entries for Neural Network-Based Disease Code Assignment
Markus Kreuzthaler, Bastian Pfeifer, Diether Kramer +1
Clinical information systems have become large repositories for semi-structured and partly annotated electronic health record data, which have reached a critical mass that makes th…
Graph-guided random forest for gene set selection
Bastian Pfeifer, Hubert Baniecki, Anna Saranti +2
Machine learning methods can detect complex relationships between variables, but usually do not exploit domain knowledge. This is a limitation because in many scientific discipline…