Construction and application of knowledge graph of Treatise on Febrile Diseases

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.

Heterogeneous graph construction and node representation learning method of Treatise on Febrile Diseases based on graph convolutional network

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.

Ye Gui and Treatise on Warm-heat Diseases

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.

Exploration and Research on Translation Strategies of Terminologies in Treatise on Warm Heat Disease

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.

The enlightenment and application of“Laxative method used in early stage of Febrile Disease”in treating COVID-19

The theory of the TCM laxative method is rich in content.Doctors of past dynasties have used it to treat febrile diseases.And the theory of“Laxative method used in early stage of Febrile Disease”has been praised by later generations.It advocates chasing away evil influence early and paying attention to the laxative method to prevent the spread of disease.the Novel Coronavirus(COVID-19)Infectious Pneumonia belongs to the category of"epidemic"in traditional Chinese medicine.The reasonable application of the cathartic is an important way to provide a way out for evil.However,don’t be blind to use laxative method,you should get it at the right time.The treatment of COVID-19 has different solution at different stages.You should adapt to the changes of the disease to use cathartic.A case in here is attached for reference.

Text Mining and Analysis of Treatise on Febrile Diseases Based on Natural Language Processing

Objective:With using natural language processing (NLP) technology to analyze and process the text of "Treatise on Febrile Diseases (TFDs)"for the sake of finding important information, this paper attempts to apply NLP in the field of text mining of traditional Chinese medicine (TCM)literature. Materials and Methods:Based on the Python language, the experiment invoked the NLP toolkit such as Jieba, nltk, gensim,and sklearn library, and combined with Excel and Word software. The text of "TFDs" was sequentially cleaned, segmented, and moved the stopped words, and then implementing word frequency statistics and analysis, keyword extraction, named entity recognition (NER) and other operations, finally calculating text similarity. Results:Jieba can accurately identify the herbal name in "TFDs." Word frequency statistics based on the word segmentation found that "warm therapy" is an important treatment of "TFDs." Guizhi decoction is the main prescription,and five core decoctions are identified. Keyword extraction based on the term "frequency-inverse document frequency" algorithm is ideal.The accuracy of NER in "TFDs" is about 86%;latent semantic indexing model calculating the similarity,"Understanding of Synopsis of Golden Chamber (SGC)" is much more similar with "SGC" than with "TFDs." The results meet expectation. Conclusions:It lays a research foundation for applying NLP to the field of text mining of unstructured TCM literature. With the combination of deep learning technology,NLP as an important branch of artificial intelligence will have broader application prospective in the field of text mining in TCM literature and construction of TCM knowledge graph as well as TCM knowledge services.

Epidemic Diseases and Chinese Medicine: Example of SARS and COVID-19: Part Two

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.

Epidemic Diseases and Chinese Medicine:Example of SARS and COVID‑19:Part Two

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.

译介学视域下中医典籍中文化负载词的英译策略研究

由于中医典籍成书年代久远,其在翻译过程中往往存在着大量的文化对应空缺词汇,因此,中医典籍中的文化负载词翻译成了一个重要的环节,也是一个难点。为了使中医文化更好、更广泛、更有效地传播,译者必须针对现实情况采取相应的对策。基于译介学理论,从文化负载词的定义出发,立足文化视角,通过对《黄帝内经》《伤寒杂病论》和《金匮要略》等中医典籍中的文化负载词的识别和解读,提出了中医文化负载词在翻译过程中需要熟练运用语言维转换、文化维转换、交际维转换等转换方法,总结了中医典籍文化负载词可以使用直译、音译/音译和注释相结合、省译或意译的方法。目的是通过中医典籍文化负载词的界定和提出的翻译策略的同时,有助于为中医文化负载词英译研究提供新的翻译视角、拓宽研究思维,旨在为解读文化差异、探寻更加合理有效的文化交流路径和方法提供新的启发和切入点,对推动中医文化负载词英译研究及中医药文化对外传播进程的加快提供有价值的参考。

外感热病共性病机及传变机制探讨

探讨外感热病共性病机及传变机制。指出外邪侵袭,导致卫气抗邪,正邪相争,阳气壅郁,从而表现出一系列的热病证候,病机特点为“郁-虚”。以“气血-体用”论概括热病证候传变规律,将热病病程概括为气、血两个阶段,其中气分阶段包括卫分等,以功能失调为主;血分统营分,以实质损害为主,兼有更加严重的功能失调。外感热病重症转化病机包括热盛动血、热闭心包、热盛动风、化源欲绝、少阴寒化及正气外脱等。

标准化病人联合情景模拟模式下伤寒琢课程教考研究

目的明晰标准化病人(SP)联合情景模拟对伤寒琢课程的教学效果。方法选择2022—2023学年南京中医药大学中医专业本科大三班级A班(61人)、B班(61人)授课,每班总课时皆为36学时;其中A班采用36课时的伤寒琢理论教学,B班在A班基础上将36课时的伤寒琢课程拆分为24课时的理论教学及12课时的SP情景模拟教学。课程结束后分别考核两班中医临床诊疗操作、医德考核、SP打分(分别占20%)以及试卷考核(占40%)。此外,对两班学生进行杰弗逊共情量表学生版(JSE-S)的问卷调查,测试其共情能力。结果两班各有2人缓考,B班中医临床诊疗操作成绩、医德考核成绩、SP打分、试卷成绩、总成绩及JSE-S评分均优于A班,差异均有统计学意义(P<0.01)。结论运用SP联合情景模拟可提高伤寒琢课程的整体教学效果,同时提高学生的共情能力。

中医视角下发热门诊2021-2022年7203例患者疾病谱研究

目的研究日常急性发热患者的疾病谱分布、发病时令、年龄、体温峰值特征。方法选取首都医科大学附属北京中医医院发热门诊,2021年1月20日(大寒节气)至2022年1月20日(大寒节气)全年就诊的急性发热患者为研究对象,总结日常急性发热患者的疾病谱分布、发病时令、年龄、体温峰值特征。结果2021年1月20日至2022年1月20日,共有7203例患者就诊于北京中医医院发热门诊,排除仅来门诊筛查且无发热等11类临床症状的患者及复诊患者4052例,最终纳入3151例初诊患者。疾病谱分布情况:上呼吸道细菌感染类疾病957例(30.37%)、感冒(非细菌感染)类疾病801例(25.42%)、胃肠道感染类疾病571例(18.12%)、肺炎等下呼吸道细菌感染类疾病446例(14.15%)、泌尿系感染类疾病149例(4.73%)、皮肤软组织感染类疾病71例(2.25%)、外科相关感染类疾病66例(2.09%)、免疫相关发热疾病27例(0.86%)、其他伴随发热的杂病63例(2.00%)。进一步研究了疾病谱前5种疾病的发病时令、年龄分布、体温峰值特点,结果发现高发时令均在夏季和冬季,不同疾病谱的多发年龄、体温峰值存在统计学差异。结论日常急性发热患者的疾病谱以肺系疾病为主(含上呼吸道细菌感染、感冒、肺炎等),其次为胃肠道和泌尿系疾病;极寒极热时令是日常急性发热性疾病的高发时令;肺炎和泌尿系感染好发于老年人群,且体温峰值较上呼吸道感染、感冒、胃肠道感染更高。

浅谈仲景胃食管反流病诊治思路

通过对《伤寒论》《金匮要略》中关于胃食管反流病相关条文的研读,归纳出胃食管反流病的临床证型,为肝胃不和证、寒热错杂证、痰气交阻证、肝郁化火证、水饮内停证、脾虚痰壅证、胃虚有热证、脾胃虚寒证、阴虚内热证。对每种证型的方药结合的临床体会进行分析,最后通过典型临床医案举隅,浅析经方治疗胃食管病的思路。

《伤寒论》《金匮要略》问诊研究

问诊是医者重要诊病技能。善问者,有条不紊并处处直指要害;不善问者,天马行空且杂乱无序。文章试结合《伤寒论》《金匮要略》来探讨问诊在临床中的应用,分别从问以获知发病诱因、问以知治疗史、问以知既往史、问以获知现症、问以指导辨证、问以知药后情况这六方面展开。在此基础上,挖掘问诊背后的思维,归纳出整体观、联系观、主次观、恒动观、除外观等思维观念。最后,介绍自拟问诊思维歌诀以助记忆,并提醒临床问诊应主动运用。希望文章所做出的工作成果能有益于中医临床。

基于六经辨病浅析柴胡桂枝干姜汤证及验案举隅

“六经辨病”指的是一种中医临床诊疗思维。即先诊断疾病,分属六经病范畴,再辨别方证,寻找方证对应线索,一一对号入座,精准用药。柴胡桂枝干姜汤证属《伤寒论》六经病中少阳病范畴,临证首先把握少阳病特点,再结合其方证要点(往来寒热、胸胁苦满、心烦、但头汗出、周身无汗、口渴而不呕、小便不利、大便溏泄等),适证选方,则药随方出。如此,病证方药,环环相扣,病下是证,证下是方,药出方下,呈无缝对接,具有精准性及可重复性,更有助提高临证有效率。

“胃家实”及三承气汤运用辨析

“胃家实”作为阳明病提纲,意义重大的同时也颇具争议。本文基于阳明胃肠的生理机制揭示“胃家实”本质,并进一步分析“胃家实”病机治法,又据此探讨三承气汤之鉴别运用、“燥屎”与大小承气汤辨证关系及“胃家实”与“脾家实”的内在联系。从而提出“胃家实”属于正阳阳明病提纲,是阳明胃肠“更虚更满”机制紊乱而形成的一种病理状态。

卞嵩京论经方汤液派六经提纲

《伤寒论》六经提纲千百年来观点林立,众说纷纭。经方汤液派,肇始于廖季平,奠基于刘民叔,发展于卞嵩京,于六经提纲有其独到见解,即“太阳病以脉浮为提纲,阳明病以腹满为提纲,少阳病以胸胁苦满为提纲,太阴病以吐利腹痛为提纲,少阴病以下利脉微细为提纲,厥阴病无提纲可言”。

基于六经方证探赜痛风的证治

痛风是因嘌呤代谢紊乱及尿酸排泄障碍而导致的异质性疾病,临床主要表现为手足关节的疼痛及痛风石的形成,现已日益成为威胁人类身体健康的常见代谢类疾病。《伤寒论》是我国医学史上影响力最广的医学著作之一,医圣张仲景以理、法、方、药为基础,开创了六经辨证体系的先河。文章执《伤寒论》六经辨证方法,结合痛风在太阳、阳明、少阳、太阴、少阴、厥阴六经中的不同临床特点,探赜痛风的六经传变规律,发掘治疗痛风的经典方剂,为临床指导痛风的辨证论治提供更广阔的思路。

基于《伤寒论》的六经辨证体系中医辨证模型推荐处方与临床医生处方结果的Kappa一致性分析

目的分析基于《伤寒论》的六经辨证体系中医辨证模型推荐处方与临床医生处方结果的一致性。方法纳入门诊患者共747例,医生通过四诊的采集得出治疗处方,再以手机终端录入采集的相关症状、体征后得到系统推荐处方。利用Kappa一致性检验来评价基于《伤寒论》的六经辨证体系中医辨证模型推荐处方与临床医生处方结果的一致性。结果基于《伤寒论》的六经辨证体系中医辨证模型推荐处方与临床医生处方的结果具有高度一致性,差异具有统计学意义(Kappa=0.71,P<0.001)。结论基于《伤寒论》的六经辨证体系中医辨证模型推荐处方与临床医生处方结果具有一致性,可辅助临床医生处方。

任达然论治温热病经验探析

任达然先生是首批全国名老中医传承指导老师,从医60余载,始终坚守临床一线,师法古贤家学,博采历代医著之精华,且能融汇贯通,对于温病的辨治独具匠心。任老擅治温热时病,精研疑难杂证,主张温热时病从痰、热、虚入手,认为温热病起病必见热象偏重,邪热鸱张,传变迅急,当须“治未病”遏阻病路,尤以温病初起时颇为效验,同时应顾护津液及胃气,正确理解并灵活应用“汗法”和“下法”,若失治误治,后果不堪,而若救治得当,则应手取效。