80 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Bernstein Center for Computational Neuroscience TübingenDE3 papers
- ETH ZurichCH3 papers
- University Hospital of BernCH2 papers
- University of BernCH2 papers
- Business and Hotel Management SchoolCH1 paper
- Cardiff UniversityGB1 paper
- Deutsche KnochenmarkspenderdateiDE1 paper
- Diabetes Center BerneCH1 paper
- Dublin City UniversityIE1 paper
- Friedrich-Alexander-Universität Erlangen-NürnbergDE1 paper
- Hertie Institute for Clinical Brain ResearchDE1 paper
- Internet SocietyUS1 paper
8 papers
Mind Companion: An Embodied Conversational Agent for Process-Based Psychotherapy
Sofie Kamber, Lukas Diebold, Pascal Riachi +3
Access to evidence-based psychotherapy remains limited worldwide, with long waitlists even in high-income regions. Recent advances in large language models (LLMs) offer potential f…
Toward Accessible Psychotherapy Training Using AI-Driven Interactive Patient Avatars
Pascal Riachi, Sofie Kamber, Stella Brogna +2
Training psychotherapists in evidence-based interventions such as Acceptance and Commitment Therapy (ACT) requires repeated practice with meaningful feedback, yet opportunities for…
Subgroup Performance Analysis in Hidden Stratifications
Alceu Bissoto, Trung-Dung Hoang, Tim Flühmann +3
Machine learning (ML) models may suffer from significant performance disparities between patient groups. Identifying such disparities by monitoring performance at a granular level…
Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific Counterfactuals
Susu Sun, Stefano Woerner, Andreas Maier +2
Interpretability is crucial for machine learning algorithms in high-stakes medical applications. However, high-performing neural networks typically cannot explain their predictions…
Tell Me Why: Explainable Public Health Fact-Checking with Large Language Models
Majid Zarharan, Pascal Wullschleger, Babak Behkam Kia +2
This paper presents a comprehensive analysis of explainable fact-checking through a series of experiments, focusing on the ability of large language models to verify public health…
A comprehensive and easy-to-use multi-domain multi-task medical imaging meta-dataset
Stefano Woerner, Arthur Jaques, Christian F. Baumgartner
While the field of medical image analysis has undergone a transformative shift with the integration of machine learning techniques, the main challenge of these techniques is often…
Cheap Learning: Maximising Performance of Language Models for Social Data Science Using Minimal Data
Leonardo Castro-Gonzalez, Yi-Ling Chung, Hannak Rose Kirk +4
The field of machine learning has recently made significant progress in reducing the requirements for labelled training data when building new models. These `cheaper' learning tech…
Stable Graphical Model Estimation with Random Forests for Discrete, Continuous, and Mixed Variables
Bernd Fellinghauer, Peter Bühlmann, Martin Ryffel +2
A conditional independence graph is a concise representation of pairwise conditional independence among many variables. Graphical Random Forests (GRaFo) are a novel method for esti…