This paper is in the following e-collection/theme issue:

Theme Issue 2022: Health Natural Language Processing and Applications (CHIP) (27) New Technologies (81) Clinical Information and Decision Making (1434) Decision Support for Health Professionals (1210) Knowledge Translation and Implementation Science (407)

Published on in Vol 10, No 9 (2022): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38414, first published .
Leveraging Representation Learning for the Construction and Application of a Knowledge Graph for Traditional Chinese Medicine: Framework Development Study

Leveraging Representation Learning for the Construction and Application of a Knowledge Graph for Traditional Chinese Medicine: Framework Development Study

Leveraging Representation Learning for the Construction and Application of a Knowledge Graph for Traditional Chinese Medicine: Framework Development Study

Authors of this article:

Heng Weng1 Author Orcid Image ;   Jielong Chen2 Author Orcid Image ;   Aihua Ou1 Author Orcid Image ;   Yingrong Lao1 Author Orcid Image
Article Authors Cited by (6) Tweetations (3) Metrics

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  1. Zhao X, Wang Y, Li P, Xu J, Sun Y, Qiu M, Pang G, Wen T. The construction of a TCM knowledge graph and application of potential knowledge discovery in diabetic kidney disease by integrating diagnosis and treatment guidelines and real-world clinical data. Frontiers in Pharmacology 2023;14 View
  2. Yang P, Wang H, Huang Y, Yang S, Zhang Y, Huang L, Zhang Y, Wang G, Yang S, He L, Huang Y. LMKG: A large-scale and multi-source medical knowledge graph for intelligent medicine applications. Knowledge-Based Systems 2024;284:111323 View
  3. Zeng J, Jia X. Systems Theory-Driven Framework for AI Integration into the Holistic Material Basis Research of Traditional Chinese Medicine. Engineering 2024;40:28 View
  4. Liu C, Li Z, Li J, Qu Y, Chang Y, Han Q, Cao L, Lin S. Research on Traditional Chinese Medicine: Domain Knowledge Graph Completion and Quality Evaluation. JMIR Medical Informatics 2024;12:e55090 View