Calculating the similarity between prescriptions to find their new indications based on graph neural network.

ABSTRACT:

Background

Drug repositioning has the potential to reduce costs and accelerate the rate of drug development, with highly promising applications. Currently, the development of artificial intelligence has provided the field with fast and efficient computing power. Nevertheless, the repositioning of traditional Chinese medicine (TCM) is still in its infancy, and the establishment of a reasonable and effective research method is a pressing issue that requires urgent attention. The use of graph neural network (GNN) to compute the similarity between TCM prescriptions to develop a method for finding their new indications is an innovative attempt.

Methods

This paper focused on traditional Chinese medicine prescriptions containing ephedra, with 20 prescriptions for treating external

SUBMITTER: Han X 

PROVIDER: S-EPMC11391787 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature