TCMRGAT: Relational graph attention networks for predicting stroke treatment efficacy of traditional Chinese medicine prescriptions

TCMRGAT aids in predicting prescription efficacy and identifying key metabolite s for stroke treatment. This study provides valuable insights into the use of Traditional Chinese Medicine for stroke and offers a promising direction for future research.

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Publication Details

Journal
Frontiers in Pharmacology
Published
2025-12-02
DOI
https://doi.org/10.3389/fphar.2025.1570094
Primary Topic
Traditional Chinese Medicine Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

TCMRGAT: Relational graph attention networks for predicting stroke treatment efficacy of traditional Chinese medicine prescriptions

Changsong Ding, Xuekun Song, Ning Cheng
Frontiers in Pharmacology
Traditional Chinese Medicine Studies
article

TCMRGAT: Relational graph attention networks for predicting stroke treatment efficacy of traditional Chinese medicine prescriptions

Changsong Ding, Xuekun Song, Ning Cheng
article en

Abstract

TCMRGAT aids in predicting prescription efficacy and identifying key metabolite s for stroke treatment. This study provides valuable insights into the use of Traditional Chinese Medicine for stroke and offers a promising direction for future research.

Frontiers in PharmacologyVol. 16
Hunan University of Traditional Chinese Medicine (CN), First Affiliated Hospital of Henan University (CN)
Openalex Percentile: Top 45%
Traditional Chinese Medicine Studies
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