Mar 31, 2019 · Modeling Drug-Disease Relations with Linguistic and Knowledge Graph Constraints. Authors:Bruno Godefroy, Christopher Potts.
It is shown that Probabilistic Soft Logic models defined over these graphs are superior to text-only and relation-only variants, and that the clinical ...
Mar 31, 2019 · We show that Probabilistic Soft Logic models defined over these graphs are superior to text-only and relation-only variants, and that the ...
Jul 8, 2024 · We use a reinforcement learning based knowledge graph completion model combined with an automatic filtering approach that produces the most ...
Modeling Drug-Disease Relations with Linguistic and Knowledge Graph Constraints. By Bruno Godefroy and Christopher Potts. FDA drug labels are rich sources of ...
Jun 15, 2023 · Computational drug repurposing models that leverage biomedical knowledge graphs to associate drugs to diseases, are biased to genes. Here, the ...
Jun 21, 2024 · In this paper, we propose TTModel, a knowledge graph embedding model for DTI prediction. By exploiting biomedical text and type information, TTModel can learn ...
Jun 5, 2024 · We propose a knowledge graph convolutional network with a heuristic search, named KGCNH, which can effectively utilize the diversity of entities and ...
Knowledge Graphs for drug repurposing: a review of databases ...
academic.oup.com › article › bbae461
Sep 26, 2024 · This review comprehensively explores some of the most prominent KGs, detailing their structure, data sources, and how they facilitate the repurposing of drugs.
We apply a knowledge graph embedding method that explicitly models the uncertainty associated with literature- derived relationships and uses link prediction to ...
Missing: Linguistic Constraints.