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cs.LG2024
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…
cs.LG2024
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…
cs.LG2024
Clustering of Disease Trajectories with Explainable Machine Learning: A Case Study on Postoperative Delirium Phenotypes
Xiaochen Zheng, Manuel Schürch, Xingyu Chen +5
The identification of phenotypes within complex diseases or syndromes is a fundamental component of precision medicine, which aims to adapt healthcare to individual patient charact…