Login / Signup

KGML-xDTD: a knowledge graph-based machine learning framework for drug treatment prediction and mechanism description.

Chunyu MaZhihan ZhouHan LiuDavid Koslicki
Published in: GigaScience (2023)
KGML-xDTD is the first model framework that can offer KG path explanations for drug repurposing predictions by leveraging the combination of prediction outcomes and existing biological knowledge and publications. We believe it can effectively reduce "black-box" concerns and increase prediction confidence for drug repurposing based on predicted path-based explanations and further accelerate the process of drug discovery for emerging diseases.
Keyphrases
  • drug discovery
  • machine learning
  • healthcare
  • transcription factor
  • type diabetes
  • emergency department
  • binding protein
  • metabolic syndrome
  • big data
  • combination therapy