Exploiting Semantic Patterns over Biomedical Knowledge Graphs for Predicting Treatment and Causative Relations

Conclusions We employed semantic graph patterns connecting pairs of candidate entities in a knowledge graph as features to predict treatment/causative relations between them. We provide what we believe is the first evidence in direct prediction of biomedical relations based on graph features. Our work complements lexical pattern based approaches in that the graph patterns can be used as additional features for weakly supervised relation prediction. Graphical abstract
Source: Journal of Biomedical Informatics - Category: Information Technology Source Type: research