Objective To establish the knowledge graph of“disease-syndrome-symptom-method-formula”in Treatise on Febrile Diseases(Shang Han Lun,《伤寒论》)for reducing the fuzziness and uncertainty of data,and for laying a foun...Objective To establish the knowledge graph of“disease-syndrome-symptom-method-formula”in Treatise on Febrile Diseases(Shang Han Lun,《伤寒论》)for reducing the fuzziness and uncertainty of data,and for laying a foundation for later knowledge reasoning and its application.Methods Under the guidance of experts in the classical formula of traditional Chinese medicine(TCM),the method of“top-down as the main,bottom-up as the auxiliary”was adopted to carry out knowledge extraction,knowledge fusion,and knowledge storage from the five aspects of the disease,syndrome,symptom,method,and formula for the original text of Treatise on Febrile Diseases,and so the knowledge graph of Treatise on Febrile Diseases was constructed.On this basis,the knowledge structure query and the knowledge relevance query were realized in a visual manner.Results The knowledge graph of“disease-syndrome-symptom-method-formula”in the Treatise on Febrile Diseases was constructed,containing 6469 entities and 10911 relational triples,on which the query of entities and their relationships can be carried out and the query result can be visualized.Conclusion The knowledge graph of Treatise on Febrile Diseases systematically realizes its digitization of the knowledge system,and improves the completeness and accuracy of the knowledge representation,and the connection between“disease-syndrome-symptom-treatment-formula”,which is conducive to the sharing and reuse of knowledge can be obtained in a clear and efficient way.展开更多
Ye Gui (courtesy name:Ye Tianshi,assumed name:Ye Xiangyan 1667-1746),a celebrated physician of the Qing Dynasty was from Wu County,Jiangsu province.Born into a TCM family and nurtured by his family tradition,he read m...Ye Gui (courtesy name:Ye Tianshi,assumed name:Ye Xiangyan 1667-1746),a celebrated physician of the Qing Dynasty was from Wu County,Jiangsu province.Born into a TCM family and nurtured by his family tradition,he read many medical classics like Huangdi's Canon of Medicine (Huang Di Nei Jing),Classic of Difficulties (Nan Jing),etc.,which laid a solid foundation for his future medical career.He was naturally bright and talented so he was good at drawing analogies.Although his medical attainments outdid his teachers,he did not become complacent.He was modest and eager to learn,so when he met any medical expert he would listen to advice with an open mind.He chose to learn from 17 super physicians,which became a favorite topic among the medical cycles.1 Since he discovered and made use of the strong points of all others and gained a thorough understanding,he advanced by leaps and bounds and his fame skyrocketed.Eventually he became a very influential medical expert.展开更多
Objective To construct symptom-formula-herb heterogeneous graphs structured Treatise on Febrile Diseases(Shang Han Lun,《伤寒论》)dataset and explore an optimal learning method represented with node attributes based o...Objective To construct symptom-formula-herb heterogeneous graphs structured Treatise on Febrile Diseases(Shang Han Lun,《伤寒论》)dataset and explore an optimal learning method represented with node attributes based on graph convolutional network(GCN).Methods Clauses that contain symptoms,formulas,and herbs were abstracted from Treatise on Febrile Diseases to construct symptom-formula-herb heterogeneous graphs,which were used to propose a node representation learning method based on GCN−the Traditional Chinese Medicine Graph Convolution Network(TCM-GCN).The symptom-formula,symptom-herb,and formula-herb heterogeneous graphs were processed with the TCM-GCN to realize high-order propagating message passing and neighbor aggregation to obtain new node representation attributes,and thus acquiring the nodes’sum-aggregations of symptoms,formulas,and herbs to lay a foundation for the downstream tasks of the prediction models.Results Comparisons among the node representations with multi-hot encoding,non-fusion encoding,and fusion encoding showed that the Precision@10,Recall@10,and F1-score@10 of the fusion encoding were 9.77%,6.65%,and 8.30%,respectively,higher than those of the non-fusion encoding in the prediction studies of the model.Conclusion Node representations by fusion encoding achieved comparatively ideal results,indicating the TCM-GCN is effective in realizing node-level representations of heterogeneous graph structured Treatise on Febrile Diseases dataset and is able to elevate the performance of the downstream tasks of the diagnosis model.展开更多
Cultural Translation Theory,originated in the 20 th century,states that the study of translation is the study of cultural in-teraction.It aims to explain that translation should not merely be constrained at traditiona...Cultural Translation Theory,originated in the 20 th century,states that the study of translation is the study of cultural in-teraction.It aims to explain that translation should not merely be constrained at traditional linguistic level,but should go to a muchbroader area,that is to say,the cultural and historical frame to direct our translation.Wen Re Lun(Treatise on Warm Heat Disease)is a representative classic of Warm Disease Theory in Traditional Chinese Medicine(TCM),with considerable cultural tradition.From the perspective of Cultural Translation Theory,this thesis discussed the translation strategy of terminologies in Wen Re Lun.The principle,"mainly based on foreignization and domestication as minor",could be preferable to transmit the TCM essence byits own language.展开更多
Along with the legends about epidemic demons,China has developed over the centuries a medical approach to epidemic diseases based on the teachings of Hucng Di Nei Jing(《黄帝内经》Huangdi s Intermnal Classic),Nan Jing...Along with the legends about epidemic demons,China has developed over the centuries a medical approach to epidemic diseases based on the teachings of Hucng Di Nei Jing(《黄帝内经》Huangdi s Intermnal Classic),Nan Jing(《难经》Classic of Difficult Issues),and Shang Han Lun(《伤寒论》Treatise on Cold Damage).Other doctors and scientists participated in this evolution of knowledge,like Wang Shuhe(王叔和),Ge Hong(葛洪),Chao Yuanfang(巢元方),Sun Simiao(孙思邈),and Liu Wansu(刘完素).However,it was in the 17^th century,after the great break of the Song,Jin,and Yuan eras that an innovative spirit,Wu Youke(吴又可1582-1652)first foresaw the existence of microorganisms as we know them now.His Wen Yi Lun(《瘟疫论》Treatise on Pestilence)foreshadows an original approach to epidemic diseases,particularly emerging infectious diseases of the 21^st century.After them,traditional Chinese medicine developed a comprehensive method of diagnosing and treating of these diseases(Epidemic Diseases Theory瘟疫学说)within the School ofHeat Diseases(温病学派).In a third article,we will examine some applications in the treatment of the SARS 2003-2004 epidemic(非典型肺炎)and the current COVID-19(新型冠状病毒肺炎)pandemic.展开更多
Along with the legends about epidemic demons,China has developed over the centuries a medical approach to epidemic diseases based on the teachings of Huang Di Nei Jing(《黄帝内经》Huangdi’s Internal Classic),Nan Jing...Along with the legends about epidemic demons,China has developed over the centuries a medical approach to epidemic diseases based on the teachings of Huang Di Nei Jing(《黄帝内经》Huangdi’s Internal Classic),Nan Jing(《难经》Classic of Difficult Issues),and Shang Han Lun(《伤寒论》Treatise on Cold Damage).Other doctors and scientists participated in this evolution of knowledge,like Wang Shuhe(王叔和),Ge Hong(葛洪),Chao Yuanfang(巢元方),Sun Simiao(孙思邈),and Liu Wansu(刘完素).However,it was in the 17th century,after the great break of the Song,Jin,and Yuan eras that an innovative spirit,Wu Youke(吴又可1582–1652)first foresaw the existence of microorganisms as we know them now.His Wen Yi Lun(《瘟疫论》Treatise on Pestilence)foreshadows an original approach to epidemic diseases,particularly emerging infectious diseases of the 21st century.After them,traditional Chinese medicine developed a comprehensive method of diagnosing and treating of these diseases(Epidemic Diseases Theory瘟疫学说)within the School of Heat Diseases(温病学派).In a third article,we will examine some applications in the treatment of the SARS 2003–2004 epidemic(非典型肺炎)and the current COVID-19(新型冠状病毒肺炎)pandemic.展开更多
基金The Open Fund of Hunan University of Traditional Chinese Medicine for the First-Class Discipline of Traditional Chinese Medicine(2018ZYX66)the Science Research Project of Hunan Provincial Department of Education(20C1391)the Natural Science Foundation of Hunan Province(2020JJ4461)。
文摘Objective To establish the knowledge graph of“disease-syndrome-symptom-method-formula”in Treatise on Febrile Diseases(Shang Han Lun,《伤寒论》)for reducing the fuzziness and uncertainty of data,and for laying a foundation for later knowledge reasoning and its application.Methods Under the guidance of experts in the classical formula of traditional Chinese medicine(TCM),the method of“top-down as the main,bottom-up as the auxiliary”was adopted to carry out knowledge extraction,knowledge fusion,and knowledge storage from the five aspects of the disease,syndrome,symptom,method,and formula for the original text of Treatise on Febrile Diseases,and so the knowledge graph of Treatise on Febrile Diseases was constructed.On this basis,the knowledge structure query and the knowledge relevance query were realized in a visual manner.Results The knowledge graph of“disease-syndrome-symptom-method-formula”in the Treatise on Febrile Diseases was constructed,containing 6469 entities and 10911 relational triples,on which the query of entities and their relationships can be carried out and the query result can be visualized.Conclusion The knowledge graph of Treatise on Febrile Diseases systematically realizes its digitization of the knowledge system,and improves the completeness and accuracy of the knowledge representation,and the connection between“disease-syndrome-symptom-treatment-formula”,which is conducive to the sharing and reuse of knowledge can be obtained in a clear and efficient way.
文摘Ye Gui (courtesy name:Ye Tianshi,assumed name:Ye Xiangyan 1667-1746),a celebrated physician of the Qing Dynasty was from Wu County,Jiangsu province.Born into a TCM family and nurtured by his family tradition,he read many medical classics like Huangdi's Canon of Medicine (Huang Di Nei Jing),Classic of Difficulties (Nan Jing),etc.,which laid a solid foundation for his future medical career.He was naturally bright and talented so he was good at drawing analogies.Although his medical attainments outdid his teachers,he did not become complacent.He was modest and eager to learn,so when he met any medical expert he would listen to advice with an open mind.He chose to learn from 17 super physicians,which became a favorite topic among the medical cycles.1 Since he discovered and made use of the strong points of all others and gained a thorough understanding,he advanced by leaps and bounds and his fame skyrocketed.Eventually he became a very influential medical expert.
基金New-Generation Artificial Intelligence-Major Program in the Sci-Tech Innovation 2030 Agenda from the Ministry of Science and Technology of China(2018AAA0102100)Hunan Provincial Department of Education key project(21A0250)The First Class Discipline Open Fund of Hunan University of Traditional Chinese Medicine(2022ZYX08)。
文摘Objective To construct symptom-formula-herb heterogeneous graphs structured Treatise on Febrile Diseases(Shang Han Lun,《伤寒论》)dataset and explore an optimal learning method represented with node attributes based on graph convolutional network(GCN).Methods Clauses that contain symptoms,formulas,and herbs were abstracted from Treatise on Febrile Diseases to construct symptom-formula-herb heterogeneous graphs,which were used to propose a node representation learning method based on GCN−the Traditional Chinese Medicine Graph Convolution Network(TCM-GCN).The symptom-formula,symptom-herb,and formula-herb heterogeneous graphs were processed with the TCM-GCN to realize high-order propagating message passing and neighbor aggregation to obtain new node representation attributes,and thus acquiring the nodes’sum-aggregations of symptoms,formulas,and herbs to lay a foundation for the downstream tasks of the prediction models.Results Comparisons among the node representations with multi-hot encoding,non-fusion encoding,and fusion encoding showed that the Precision@10,Recall@10,and F1-score@10 of the fusion encoding were 9.77%,6.65%,and 8.30%,respectively,higher than those of the non-fusion encoding in the prediction studies of the model.Conclusion Node representations by fusion encoding achieved comparatively ideal results,indicating the TCM-GCN is effective in realizing node-level representations of heterogeneous graph structured Treatise on Febrile Diseases dataset and is able to elevate the performance of the downstream tasks of the diagnosis model.
文摘Cultural Translation Theory,originated in the 20 th century,states that the study of translation is the study of cultural in-teraction.It aims to explain that translation should not merely be constrained at traditional linguistic level,but should go to a muchbroader area,that is to say,the cultural and historical frame to direct our translation.Wen Re Lun(Treatise on Warm Heat Disease)is a representative classic of Warm Disease Theory in Traditional Chinese Medicine(TCM),with considerable cultural tradition.From the perspective of Cultural Translation Theory,this thesis discussed the translation strategy of terminologies in Wen Re Lun.The principle,"mainly based on foreignization and domestication as minor",could be preferable to transmit the TCM essence byits own language.
文摘Along with the legends about epidemic demons,China has developed over the centuries a medical approach to epidemic diseases based on the teachings of Hucng Di Nei Jing(《黄帝内经》Huangdi s Intermnal Classic),Nan Jing(《难经》Classic of Difficult Issues),and Shang Han Lun(《伤寒论》Treatise on Cold Damage).Other doctors and scientists participated in this evolution of knowledge,like Wang Shuhe(王叔和),Ge Hong(葛洪),Chao Yuanfang(巢元方),Sun Simiao(孙思邈),and Liu Wansu(刘完素).However,it was in the 17^th century,after the great break of the Song,Jin,and Yuan eras that an innovative spirit,Wu Youke(吴又可1582-1652)first foresaw the existence of microorganisms as we know them now.His Wen Yi Lun(《瘟疫论》Treatise on Pestilence)foreshadows an original approach to epidemic diseases,particularly emerging infectious diseases of the 21^st century.After them,traditional Chinese medicine developed a comprehensive method of diagnosing and treating of these diseases(Epidemic Diseases Theory瘟疫学说)within the School ofHeat Diseases(温病学派).In a third article,we will examine some applications in the treatment of the SARS 2003-2004 epidemic(非典型肺炎)and the current COVID-19(新型冠状病毒肺炎)pandemic.
文摘Along with the legends about epidemic demons,China has developed over the centuries a medical approach to epidemic diseases based on the teachings of Huang Di Nei Jing(《黄帝内经》Huangdi’s Internal Classic),Nan Jing(《难经》Classic of Difficult Issues),and Shang Han Lun(《伤寒论》Treatise on Cold Damage).Other doctors and scientists participated in this evolution of knowledge,like Wang Shuhe(王叔和),Ge Hong(葛洪),Chao Yuanfang(巢元方),Sun Simiao(孙思邈),and Liu Wansu(刘完素).However,it was in the 17th century,after the great break of the Song,Jin,and Yuan eras that an innovative spirit,Wu Youke(吴又可1582–1652)first foresaw the existence of microorganisms as we know them now.His Wen Yi Lun(《瘟疫论》Treatise on Pestilence)foreshadows an original approach to epidemic diseases,particularly emerging infectious diseases of the 21st century.After them,traditional Chinese medicine developed a comprehensive method of diagnosing and treating of these diseases(Epidemic Diseases Theory瘟疫学说)within the School of Heat Diseases(温病学派).In a third article,we will examine some applications in the treatment of the SARS 2003–2004 epidemic(非典型肺炎)and the current COVID-19(新型冠状病毒肺炎)pandemic.