Figure 1.

Flowchart of the learning method. Each level of the cascade consists of deep survival forests, which directly learn cancer prognosis prediction with multiple decision trees. All connected features will be optimized to obtain a more compact feature set and then transferred to the next level. Our model can use both labeled and unlabeled datasets. Deep survival forest can labels unlabeled data to augmented training datasets.