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Decision-Making System for the Diagnosis of Syndrome Based on Traditional Chinese Medicine Knowledge Graph

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...

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Autores principales: Yang, Rui, Ye, Qing, Cheng, Chunlei, Zhang, Suhua, Lan, Yong, Zou, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8853781/
https://www.ncbi.nlm.nih.gov/pubmed/35186106
http://dx.doi.org/10.1155/2022/8693937
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author Yang, Rui
Ye, Qing
Cheng, Chunlei
Zhang, Suhua
Lan, Yong
Zou, Jing
author_facet Yang, Rui
Ye, Qing
Cheng, Chunlei
Zhang, Suhua
Lan, Yong
Zou, Jing
author_sort Yang, Rui
collection PubMed
description 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%.
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spelling pubmed-88537812022-02-18 Decision-Making System for the Diagnosis of Syndrome Based on Traditional Chinese Medicine Knowledge Graph Yang, Rui Ye, Qing Cheng, Chunlei Zhang, Suhua Lan, Yong Zou, Jing Evid Based Complement Alternat Med Research Article 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%. Hindawi 2022-02-10 /pmc/articles/PMC8853781/ /pubmed/35186106 http://dx.doi.org/10.1155/2022/8693937 Text en Copyright © 2022 Rui Yang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yang, Rui
Ye, Qing
Cheng, Chunlei
Zhang, Suhua
Lan, Yong
Zou, Jing
Decision-Making System for the Diagnosis of Syndrome Based on Traditional Chinese Medicine Knowledge Graph
title Decision-Making System for the Diagnosis of Syndrome Based on Traditional Chinese Medicine Knowledge Graph
title_full Decision-Making System for the Diagnosis of Syndrome Based on Traditional Chinese Medicine Knowledge Graph
title_fullStr Decision-Making System for the Diagnosis of Syndrome Based on Traditional Chinese Medicine Knowledge Graph
title_full_unstemmed Decision-Making System for the Diagnosis of Syndrome Based on Traditional Chinese Medicine Knowledge Graph
title_short Decision-Making System for the Diagnosis of Syndrome Based on Traditional Chinese Medicine Knowledge Graph
title_sort decision-making system for the diagnosis of syndrome based on traditional chinese medicine knowledge graph
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8853781/
https://www.ncbi.nlm.nih.gov/pubmed/35186106
http://dx.doi.org/10.1155/2022/8693937
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