ORIGINAL RESEARCH
Accepted on 15 Apr 2025
AMFGNN:An adaptive multi-view fusion graph neural network model for drug prediction
doi 10.3389/fphar.2025.1543966
- 239 views
- Frontiers in Pharmacology
- Ethnopharmacology
- Research Topics
- Artificial Intelligence in Traditional Medicine Research and Application
Artificial Intelligence in Traditional Medicine Research and Application
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Articles
REVIEW
Published on 15 Apr 2025
Artificial intelligence in traditional Chinese medicine: advances in multi-metabolite multi-target interaction modeling
doi 10.3389/fphar.2025.1541509
- 479 views
REVIEW
Published on 08 Apr 2025
Digital intelligence technology: new quality productivity for precision traditional Chinese medicine
doi 10.3389/fphar.2025.1526187
- 385 views
BRIEF RESEARCH REPORT
Published on 03 Mar 2025
SysNatMed: rational natural medicine discovery by systems genetics
doi 10.3389/fphar.2025.1496061
- 674 views
ORIGINAL RESEARCH
Published on 24 Feb 2025
Structural analysis and treatment of acute liver injury of polysaccharides from the Radix Actinidiae Chinensis
doi 10.3389/fphar.2025.1544302
- 562 views
ORIGINAL RESEARCH
Published on 21 Feb 2025
Predicting new-onset stroke with machine learning: development of a model integrating traditional Chinese and western medicine
doi 10.3389/fphar.2025.1546878
- 673 views
ORIGINAL RESEARCH
Published on 19 Feb 2025
TCMRD - KG: innovative design and development of rheumatology knowledge graph in ancient Chinese literature assisted by large language models
doi 10.3389/fphar.2025.1535596
- 762 views
ORIGINAL RESEARCH
Published on 07 Jan 2025
Research on a traditional Chinese medicine case-based question-answering system integrating large language models and knowledge graphs
doi 10.3389/fmed.2024.1512329
- 1,891 views
ORIGINAL RESEARCH
Published on 06 Jan 2025
Accurate identification of snoRNA targets using variational graph autoencoder to advance the redevelopment of traditional medicines
doi 10.3389/fphar.2024.1529128
- 600 views
ORIGINAL RESEARCH
Published on 22 Oct 2024
MKAN-MMI: empowering traditional medicine-microbe interaction prediction with masked graph autoencoders and KANs
doi 10.3389/fphar.2024.1484639
- 798 views
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