• Corpus ID: 9507846

Stratification of patient trajectories using covariate latent variable models

@article{Campbell2016StratificationOP,
  title={Stratification of patient trajectories using covariate latent variable models},
  author={Kieran R. Campbell and Christopher Yau},
  journal={arXiv: Machine Learning},
  year={2016}
}
Standard models assign disease progression to discrete categories or stages based on well-characterized clinical markers. However, such a system is potentially at odds with our understanding of the underlying biology, which in highly complex systems may support a (near-)continuous evolution of disease from inception to terminal state. To learn such a continuous disease score one could infer a latent variable from dynamic "omics" data such as RNA-seq that correlates with an outcome of interest… 

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