Fig. 1.

Structure of an interpretable artificial neural network. The input layer is followed by an additional pathway layer, where each node corresponds to a known molecular pathway. If a molecule is known to be involved in a pathway, a connection is made between the two. Hence, important pathways implicated in the outcome are activated with bigger weights during training. Figure inspired from Deng et al. (2020)[73].