ArticleEvidence-based complementary and alternative medicine : eCAM2022
Decision-Making System for the Diagnosis of Syndrome Based on Traditional Chinese Medicine Knowledge Graph.
Article in Evidence-based complementary and alternative medicine : eCAM, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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The trial behind it
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Pooled it
- Artificial Intelligence for Spleen-Stomach Disorders in Traditional Chinese Medicine: Integrating Knowledge Graphs with Intelligent Diagnosis and Treatment.Current medical science · 2025Review
- Relational subgraphs fused with complete subgraphs based on the knowledge graph for mining protein complexes.Scientific reports · 2025Article
- Machine learning algorithms predict breast cancer incidence risk: a data-driven retrospective study based on biochemical biomarkers.BMC cancer · 2025Article
- KGSD-Net: a knowledge graph syndrome differentiation network for syndrome classification.Frontiers in medicine · 2025Article
- Explainable AI Method for Tinnitus Diagnosis via Neighbor-Augmented Knowledge Graph and Traditional Chinese Medicine: Development and Validation Study.JMIR medical informatics · 2024Article
- A new model construction based on the knowledge graph for mining elite polyphenotype genes in crops.Frontiers in plant science · 2024Article
- Knowledge graph construction for heart failure using large language models with prompt engineering.Frontiers in computational neuroscience · 2024Article
- Research on a traditional Chinese medicine case-based question-answering system integrating large language models and knowledge graphs.Frontiers in medicine · 2024Article
- [Knowledge Graph-Based Prediction of Potentially Inappropriate Medication].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2023Article
- Combining the External Medical Knowledge Graph Embedding to Improve the Performance of Syndrome Differentiation Model.Evidence-based complementary and alternative medicine : eCAM · 2023Article
- Healthcare knowledge graph construction: A systematic review of the state-of-the-art, open issues, and opportunities.Journal of big data · 2023Article
- Knowledge-Based Recurrent Neural Network for TCM Cerebral Palsy Diagnosis.Evidence-based complementary and alternative medicine : eCAM · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The clinical informatization of traditional Chinese medicine (TCM) focuses on serving users and assisting in diagnosis. The rules of clinical knowledge play an important role in improving the TCM informatization service. However, many rules are difficult to find because of the complexity of the data in the current TCM syndrome prediction. Therefore, we proposed an end-to-end model, called Decision-making System for the Diagnosis of Syndrome (DSDS), which is based on the knowledge graph (KG) of TCM. This paper introduces the link prediction for the diagnosis of syndrome by dismantling medical records into multiple symptoms. In addition, based on the symptoms and predicted syndromes, the most relevant syndrome could be determined by the scoring and voting method in this paper. The results show that the accuracy of DSDS is 80.6%.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.