2 citations · 3 across the 3 of their papers we have counts for
3 papers
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…
Detect-and-Segment: a Deep Learning Approach to Automate Wound Image Segmentation
Gaetano Scebba, Jia Zhang, Sabrina Catanzaro +4
Chronic wounds significantly impact quality of life. If not properly managed, they can severely deteriorate. Image-based wound analysis could aid in objectively assessing the wound…