6 citations · 13 across the 16 of their papers we have counts for
4 papers · 1 filter
Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker Identification
Michael Vollenweider, Manuel Schürch, Chiara Rohrer +3
Precision medicine has the potential to tailor treatment decisions to individual patients using machine learning (ML) and artificial intelligence (AI), but it faces significant cha…
Rethinking Molecular Design: Integrating Latent Variable and Auto-Regressive Models for Goal Directed Generation
Heath Arthur-Loui, Amina Mollaysa, Michael Krauthammer
De novo molecule design has become a highly active research area, advanced significantly through the use of state-of-the-art generative models. Despite these advances, several fund…
Semi-Supervised Generative Models for Disease Trajectories: A Case Study on Systemic Sclerosis
Cécile Trottet, Manuel Schürch, Ahmed Allam +11
We propose a deep generative approach using latent temporal processes for modeling and holistically analyzing complex disease trajectories, with a particular focus on Systemic Scle…
Towards AI-Based Precision Oncology: A Machine Learning Framework for Personalized Counterfactual Treatment Suggestions based on Multi-Omics Data
Manuel Schürch, Laura Boos, Viola Heinzelmann-Schwarz +4
AI-driven precision oncology has the transformative potential to reshape cancer treatment by leveraging the power of AI models to analyze the interaction between complex patient ch…