A deep state-space analysis framework for cancer patient latent state estimation and classification from EHR time-series data
Fig 2
(a) The differences in the distribution of endpoints over the time-series of latent states for deceased patients (red) and surviving patients (blue) are shown.
(b) The results of patient stratification and the number of endpoints for deceased and surviving patients in each cluster are shown. Cluster I (red), Cluster II (yellow), and Cluster III (green) correspond to the dangerous state, the intermediate state, and the stable state, respectively. (c) The state transitions for deceased and surviving patients are shown as an example. The blue plots represent the latent states of patients across all time-series, the color bar indicates the number of days elapsed from the endpoint, and the plots change from white to red, and from red to black over time. The example state transitions for deceased patients show transitions from cluster III to II to I, while the example for surviving patients shows transitions back and forth between clusters III and II. (d) The transition probabilities between the three clusters for deceased and surviving patients. The thickness of the lines between the clusters represents the magnitude of the probability.