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…
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…
Modeling Complex Disease Trajectories using Deep Generative Models with Semi-Supervised Latent Processes
Cécile Trottet, Manuel Schürch, Ahmed Allam +6
In this paper, we propose a deep generative time series approach using latent temporal processes for modeling and holistically analyzing complex disease trajectories. We aim to fin…
Two-Stage Aggregation with Dynamic Local Attention for Irregular Time Series
Xingyu Chen, Xiaochen Zheng, Amina Mollaysa +3
Irregular multivariate time series data is characterized by varying time intervals between consecutive observations of measured variables/signals (i.e., features) and varying sampl…