In terms of relation extraction, Deep Learning (38,45), LSTM (40,43), and GNN (42) were the machine learning mod-
els most commonly used in pre-model AI systems. The authors of (48) incorporated background knowledge about gene
function, associated pathways, known drug targets, and cancer cell type into a Relational Learning (LR) model and an
Aleph inductive logic programming engine based on a breadth-first search to learn and understand the mechanisms of
cancer drugs. Our review revealed no studies wherein KGs were used for inference and reasoning in the pre-model XAI
system, thus indicating that reasoning is usually applied after developing machine learning models.
Knowledge-graph-based explainable AI- A systematic review