Learning temporal difference embeddings for biomedical hypothesis generation.
Journal:
Bioinformatics (Oxford, England)
Published Date:
Nov 30, 2022
Abstract
MOTIVATION: Hypothesis generation (HG) refers to the discovery of meaningful implicit connections between disjoint scientific terms, which is of great significance for drug discovery, prediction of drug side effects and precision treatment. More recently, a few initial studies attempt to model the dynamic meaning of the terms or term pairs for HG. However, most existing methods still fail to accurately capture and utilize the dynamic evolution of scientific term relations.