Exploring the rules of Li-Fa-Fang-Yao on diabetes mellitus within traditional Chinese medicine through text mining
Diabetes mellitus, or simply diabetes, is a group of metabolic diseases in which a person has high blood sugar, either because the body does not produce enough insulin, or because cells do not respond to the insulin that is produced. In traditional Chinese medicine (TCM), diabetes mellitus is called...
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creator | Yunyu Huang Shidong Wang Lianjie Wang Xiuchen Yu Miao Jiang Junping Zhan Aiping Lu Guang Zheng |
description | Diabetes mellitus, or simply diabetes, is a group of metabolic diseases in which a person has high blood sugar, either because the body does not produce enough insulin, or because cells do not respond to the insulin that is produced. In traditional Chinese medicine (TCM), diabetes mellitus is called "Sweet Urine Disease". Over several thousand years of clinical research and theoretical thoughts, some treatment on diabetes has been accumulated. These treatment rules can be demonstrated through the networks of Li-Fa-Fang-Yao which is of critical importance in clinical practices of TCM. Li-Fa-Fang-Yao, which means principles, methods, formulae, and Chinese herbal medicines respectively, indicate the four basic steps of diagnosis and treatment: determining the cause, mechanism and location of the disease according to the medical theories and principles, then deciding the treatment principle and method, and finally selecting a formula as well as proper Chinese herbal medicines. In this paper, focused on disease of diabetes, we explored the rules of Li-Fa-Fang-Yao within the framework of traditional Chinese medicine. Through calculation, four networks i.e., symptom, pattern/syndrome, treatment principle, herbal formula, and Chinese herbal medicine were constructed. Based on these four networks, their connections were also demonstrated by the professional knowledge of TCM and thus a whole network of Li-Fa-Fang-Yao was constructed and demonstrated. This Li-Fa-Fang-Yao network might be meaningful for both clinical practise and medical research. |
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In traditional Chinese medicine (TCM), diabetes mellitus is called "Sweet Urine Disease". Over several thousand years of clinical research and theoretical thoughts, some treatment on diabetes has been accumulated. These treatment rules can be demonstrated through the networks of Li-Fa-Fang-Yao which is of critical importance in clinical practices of TCM. Li-Fa-Fang-Yao, which means principles, methods, formulae, and Chinese herbal medicines respectively, indicate the four basic steps of diagnosis and treatment: determining the cause, mechanism and location of the disease according to the medical theories and principles, then deciding the treatment principle and method, and finally selecting a formula as well as proper Chinese herbal medicines. In this paper, focused on disease of diabetes, we explored the rules of Li-Fa-Fang-Yao within the framework of traditional Chinese medicine. Through calculation, four networks i.e., symptom, pattern/syndrome, treatment principle, herbal formula, and Chinese herbal medicine were constructed. Based on these four networks, their connections were also demonstrated by the professional knowledge of TCM and thus a whole network of Li-Fa-Fang-Yao was constructed and demonstrated. 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In traditional Chinese medicine (TCM), diabetes mellitus is called "Sweet Urine Disease". Over several thousand years of clinical research and theoretical thoughts, some treatment on diabetes has been accumulated. These treatment rules can be demonstrated through the networks of Li-Fa-Fang-Yao which is of critical importance in clinical practices of TCM. Li-Fa-Fang-Yao, which means principles, methods, formulae, and Chinese herbal medicines respectively, indicate the four basic steps of diagnosis and treatment: determining the cause, mechanism and location of the disease according to the medical theories and principles, then deciding the treatment principle and method, and finally selecting a formula as well as proper Chinese herbal medicines. In this paper, focused on disease of diabetes, we explored the rules of Li-Fa-Fang-Yao within the framework of traditional Chinese medicine. Through calculation, four networks i.e., symptom, pattern/syndrome, treatment principle, herbal formula, and Chinese herbal medicine were constructed. Based on these four networks, their connections were also demonstrated by the professional knowledge of TCM and thus a whole network of Li-Fa-Fang-Yao was constructed and demonstrated. 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In traditional Chinese medicine (TCM), diabetes mellitus is called "Sweet Urine Disease". Over several thousand years of clinical research and theoretical thoughts, some treatment on diabetes has been accumulated. These treatment rules can be demonstrated through the networks of Li-Fa-Fang-Yao which is of critical importance in clinical practices of TCM. Li-Fa-Fang-Yao, which means principles, methods, formulae, and Chinese herbal medicines respectively, indicate the four basic steps of diagnosis and treatment: determining the cause, mechanism and location of the disease according to the medical theories and principles, then deciding the treatment principle and method, and finally selecting a formula as well as proper Chinese herbal medicines. In this paper, focused on disease of diabetes, we explored the rules of Li-Fa-Fang-Yao within the framework of traditional Chinese medicine. Through calculation, four networks i.e., symptom, pattern/syndrome, treatment principle, herbal formula, and Chinese herbal medicine were constructed. Based on these four networks, their connections were also demonstrated by the professional knowledge of TCM and thus a whole network of Li-Fa-Fang-Yao was constructed and demonstrated. This Li-Fa-Fang-Yao network might be meaningful for both clinical practise and medical research.</abstract><pub>IEEE</pub><tpages>5</tpages></addata></record> |
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subjects | diabetes mellitus Li-Fa-Fang-Yao network text mining traditional Chinese medicine |
title | Exploring the rules of Li-Fa-Fang-Yao on diabetes mellitus within traditional Chinese medicine through text mining |
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