scholarly journals Professor Ruixia Pei’s Experience in Treating Hyperthyroidism

2021 ◽  
Vol 5 (4) ◽  
pp. 64-66
Author(s):  
Fen Zhang ◽  
Xingyu Chen ◽  
Di Sun ◽  
Ruixia Pei
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Clinical Experience ◽  
Clinical Treatment ◽  
Diagnosis And Treatment ◽  
Shaanxi Province ◽  
Syndrome Differentiation ◽  
Traditional Chinese Medicine Practitioner ◽  
Syndrome Differentiation And Treatment ◽  
Medication Experience

In this article, we summarize the clinical experience of Professor Ruixia Pei, a famous traditional Chinese medicine practitioner in Shaanxi Province, China, in treating hyperthyroidism. The etiology and pathogenesis, syndrome differentiation, and medication experience are introduced in detail. This paper summarizes the advantages of Professor Pei’s methods of syndrome differentiation and treatment of hyperthyroidism. This may help enrich the clinical treatment of hyperthyroidism, and provide some diagnosis and treatment ideas.

scholarly journals Analysis of Zhang Hongxing's Clinical Experience in Treating Chronic Cough

2021 ◽  
Vol 5 (3) ◽  
Author(s):  
Wenguang Zheng ◽  
Hongxing Zhang
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Clinical Experience ◽  
Human Body ◽  
Chronic Cough ◽  
Treatment Effects ◽  
Shandong Province ◽  
Clinical Treatment ◽  
Considerable Experience

Director Zhang Hongxing is a famous traditional Chinese medicine (TCM) doctor in Shandong province and a teacher in the Famous TCM Expert Studio in Dezhou city. He has rich clinical experience and considerable experience in the treatment of common clinical chronic coughs. Director Zhang Hongxing believes that chronic cough belongs to the category of "wind cough" and "long-term cough" according to TCM. TCM diagnosis should start from the four aspects of "wind evil residing in lung", "liver", "spleen and stomach", and "yang deficiency". Starting from viewing the human body as an organic whole, distinguish between deficiency or excess in cold and heat, and clinical treatment for cough should focus on dispelling "wind", regulating the functions of liver, spleen, and stomach, and supplementing the body's yang. Formulate treatment based on different categorization, and modify prescription according to the symptoms, and the treatment effects are remarkable.

scholarly journals Research Progress of TCM Treatment of Uterine Fibroids

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Xiaoyu Lu ◽  
Xinjie Hu ◽  
Mei Chen
Keyword(s):  
Chinese Medicine ◽  
Side Effects ◽  
Traditional Chinese Medicine ◽  
Uterine Fibroids ◽  
Research Progress ◽  
Syndrome Differentiation ◽  
Benign Tumors ◽  
Syndrome Differentiation And Treatment

Uterine fibroids are the most common benign tumors in gynecology. Traditional Chinese medicine treats uterine fibroids according to syndrome differentiation and treatment. The treatment of uterine fibroids has the characteristics of definitive curative effects and minor side-effects, but there are also many shortcomings, which require more in-depth research and exploration.

scholarly journals Research on the diagnosis and treatment of the dominant diseases of traditional Chinese medicine based on machine learning

2020 ◽  
Author(s):  
yuqi tang ◽  
Dongdong Yang ◽  
Zechen Li ◽  
Yu Fang ◽  
Shanshan Gao
Keyword(s):  
Machine Learning ◽  
Chinese Medicine ◽  
Random Forest ◽  
Traditional Chinese Medicine ◽  
Hierarchical Cluster ◽  
Diagnostic Methods ◽  
Diagnosis And Treatment ◽  
Syndrome Differentiation ◽  
The Novel ◽  
Sample Data

Abstract Background: Insomnia as one of the dominant diseases of traditional Chinese medicine (TCM) has been extensively studied in recent years. To explore the novel approaches of research on TCM diagnosis and treatment, this paper presents a strategy for the research of insomnia based on machine learning. Methods: First of all, 654 insomnia cases have been collected from an experienced doctor of TCM as sample data. Secondly, in the light of the characteristics of TCM diagnosis and treatment, the contents of research samples have been divided into four parts: the basic information, the four diagnostic methods, the treatment based on syndrome differentiation and the main prescription. And then, these four parts have been analyzed by three analysis methods, including frequency analysis, association rules and hierarchical cluster analysis. Finally, a comprehensive study of the whole four parts has been conducted by random forest. Results: Researches of the above four parts revealed some essential connections. Simultaneously, based on the algorithm model established by the random forest, the accuracy of predicting the main prescription by the combination of the four diagnostic methods and the treatment based on syndrome differentiation was 0.85. Furthermore, having been extracted features through applying the random forest, the syndrome differentiation of five zang-organs was proven to be the most significant parameter of the TCM diagnosis and treatment.Conclusions: The results indicate that the machine learning methods are worthy of being adopted to study the dominant diseases of TCM for exploring the crucial rules of the diagnosis and treatment.

scholarly journals Professor Xiaoquan Du’s Seven Methods of Treating Stomachache

2021 ◽  
Vol 5 (4) ◽  
pp. 117-120
Author(s):  
Xuzhao Wang ◽  
Li Liu ◽  
Xiaoquan Du ◽  
Chunxia Ma ◽  
Wei Cui
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Clinical Diagnosis ◽  
Diagnosis And Treatment ◽  
Syndrome Differentiation ◽  
Main Symptom ◽  
Stomach Diseases ◽  
Characteristic Methods ◽  
Tcm Syndrome

Stomachache is the main symptom of stomach duct pain near the heart. Professor Xiaoquan Du is experienced in treating spleen and stomach diseases with traditional Chinese medicine (TCM) syndrome differentiation. He has vast practical TCM experience through years of clinical diagnosis and treatment, and incorporated his own characteristic methods in treatments, thereby developing seven methods for the treatment of stomachache. Clinically, methods such as “invigorating the spleen and benefiting the stomach” and “warming the middle and dispersing cold” are mostly adopted to treat stomach duct pain.

A Traditional Chinese Medicine Syndrome Classification Model based on Cross-FGCNN: Model Development and Validation (Preprint)

2021 ◽  
Author(s):  
Zonghai Huang ◽  
Ju Chen ◽  
Yanmei Zhong ◽  
Simin Yang ◽  
Yiyi Ma ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Model Development ◽  
Classification Model ◽  
Syndrome Differentiation ◽  
Traditional Chinese Medicine Syndrome ◽  
Nonlinear Features ◽  
Syndrome Differentiation And Treatment ◽  
Development And Validation ◽  
Multi Classification

UNSTRUCTURED Syndrome differentiation and treatment is the core of traditional Chinese medicine(TCM) in the treatment of diseases. TCM doctors can dialectically classify the syndrome according to the patients' symptoms and conduct treatment. Syndrome differentiation can be regarded as a mathematical model for multi-classification of different high-dimensional sparse symptom vectors. The FGCNN can quickly and effectively extract the nonlinear cross features of sparse vectors in the CTR task. On this basis, we selected the data of 5273 real cases of dysmenorrhea and divided the symptoms into field according to the four diagnosis of TCM, so as to construct an improved Cross-FGCNN model and apply it to the intelligent dialectics of TCM. We used 6 kinds of intelligent dialectical models and 3 kinds of CTR models as comparisons at the same time. Cross-FGCNN can achieve 96.21% accuracy and 0.836 Log-Loss, which is better than other models. We maintain that the model of Cross-FGCNN can automatically extract the linear and nonlinear features of symptoms and classify them, having great potential in the intelligent dialectics of TCM in the future.

Analysis of Traditional Chinese Medicine Diagnosis and Treatment Strategies for COVID-19 Based on “The Diagnosis and Treatment Program for Coronavirus Disease-2019” from Chinese Authority

2020 ◽  
Vol 48 (05) ◽  
pp. 1035-1049 ◽  
Author(s):  
Zhi-Hui Zhao ◽  
Yi Zhou ◽  
Wei-Hong Li ◽  
Qing-Song Huang ◽  
Zhao-Hui Tang ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Treatment Program ◽  
Recovery Period ◽  
Treatment Strategies ◽  
The Body ◽  
Diagnosis And Treatment ◽  
Syndrome Differentiation ◽  
Chinese Government ◽  
Chinese Authority

In December 2019, coronavirus disease-2019 (COVID-19) broke out in Wuhan and other places. Seven versions of the Diagnosis and Treatment Program for Coronavirus Disease-2019 successively issued by the Chinese government have designated traditional Chinese medicine (TCM) as a necessary medical strategy. Based on the changes in TCM diagnosis and treatment strategies in these seven versions of Diagnosis and Treatment Program for Coronavirus Disease-2019, this paper collected data reported by the Chinese government media; analyzed the understanding of the etiology, pathogenesis, syndrome differentiation, treatment methods, and prescriptions of COVID-19 by TCM and evaluated the clinical efficacy of TCM strategies. COVID-19 is associated with TCM disease of pestilence, and its pathogenesis can be summarized as an “epidemic pathogen invading the body, followed by entering the internal organs and transforming into heat, resulting in pathogen trapping in the interior and healthy qi collapsing, and deficiency of qi and yin”. Pathological processes should be emphasized in syndrome differentiation. The manifestations of qi deficiency and yin deficiency are exhibited during the recovery period. TCM strategies represented by Qing Fei Pai Du Tang have shown apparent advantages in improving symptoms, promoting virus clearance, and shortening hospitalization, as well as surprising efficacy of zero patient progressing from mild to severe cases in a TCM cabin hospital. Clinical data illustrate the effectiveness of TCM strategies proposed by the Chinese government. This major epidemic may bring new opportunities for TCM development.

scholarly journals Potential Therapeutic Effect of Traditional Chinese Medicine on Coronavirus Disease 2019: A Review

2020 ◽  
Vol 11 ◽  
Author(s):  
Qin Qiu ◽  
Yuge Huang ◽  
Xiaohua Liu ◽  
Fangfang Huang ◽  
Xiaoling Li ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Severe Acute Respiratory Syndrome ◽  
Small Molecules ◽  
Prevention And Control ◽  
Clinical Manifestations ◽  
Syndrome Differentiation ◽  
Treatment Measures ◽  
Syndrome Differentiation And Treatment ◽  
And Control

The Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 has been rapidly spreading globally and has caused worldwide social and economic disruption. Currently, no specific antiviral drugs or clinically effective vaccines are available to prevent and treat COVID-19. Traditional Chinese medicine (TCM) can facilitate syndrome differentiation and treatment according to the clinical manifestations of patients and has demonstrated effectiveness in epidemic prevention and control. In China, TCM intervention has helped to control the epidemic; however, TCM has not been fully recognized worldwide. In this review, we summarize the epidemiology and etiological characteristics of severe acute respiratory syndrome coronavirus 2 and the prevention and treatment measures of COVID-19. Additionally, we describe the application of TCM in the treatment of COVID-19 and the identification of small molecules of TCM that demonstrate anti-coronavirus activity. We also analyze the current problems associated with the recognition of TCM. We hope that, through the contribution of TCM, combined with modern technological research and the support of our international counterparts, COVID-19 can be effectively controlled and treated.

scholarly journals Towards an Ontology-Based Decision Support System for Syndrome-Differentiation and Treatment of Psoriasis Vulgaris in Traditional Chinese Medicine

2020 ◽  
Author(s):  
Hai Long ◽  
Zhe Wang ◽  
Yidi Cui ◽  
Junhui Wang ◽  
Bo Gao ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Decision Support ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Psoriasis Vulgaris ◽  
Domain Ontology ◽  
Approximate Reasoning ◽  
Syndrome Differentiation ◽  
Syndrome Differentiation And Treatment ◽  
Tcm Syndrome

Abstract Background: Psoriasis is a chronic, non-communicable, painful, disfiguring and disabling disease, which is not curable and strongly declines the patients’ quality of life (QoL). However, diagnose and treatment in traditional Chinese medicine (TCM) based on syndrome differentiation has been used in practice for a long time and has also achieved some effect. Though, up to now, only few studies are available reporting on the use of semantic technologies and pertain to knowledge systems that use TCM-syndrome differentiation for information retrieval and automated reasoning. Nowadays, the diagnosis in TCM relies mainly on the personal expertise and clinical experience of the doctors. For various reasons, misdiagnoses or missed diagnoses cannot be completely excluded, leading to unexpected results.Methods: Firstly, we developed a domain ontology for syndrome differentiation of psoriasis vulgaris. For this purpose, we used the ontology editor Protégé and applied a top-down approach which adopts the framework of general formal ontology (GFO) and its middle-level core ontology GFO-TCM. Furthermore, we implement a prototype which is based on this ontology. Additionally, we also used a case-database for CBR (Case Based Reasoning) combined with fuzzy pattern recognition.Results: A prototype for diagnosis and treatment of psoriasis vulgaris, named ONTOPV-system, is proposed which is based on the principle of syndrome differentiation and treatment in TCM; this system realizes an expert-assisted decision support method which relies on a domain ontology, uses fuzzy logic reasoning, and case retrieval and is intended to support clinical diagnostic decisions for TCM practitioners.Conclusions: We designed and implemented a prototype for psoriasis diagnosis in terms of syndrome differentiation. The system can not only realize the basic functionalities of data collection, querying, browsing and navigation, but also support rule-based knowledge reasoning and customize approximate reasoning based on CBR through fuzzy logic, which can provide users with clinical decision support for TCM syndrome differentiation in diagnosis of psoriasis. In addition, it comprises a domain knowledge base of psoriasis, which is developed based on the GFO framework with good extensibility.

scholarly journals Research of insomnia on traditional Chinese medicine diagnosis and treatment based on machine learning

2020 ◽  
Author(s):  
Yuqi Tang ◽  
Zechen Li ◽  
Dongdong Yang ◽  
Yu Fang ◽  
Shanshan Gao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Chinese Medicine ◽  
Random Forest ◽  
Traditional Chinese Medicine ◽  
Hierarchical Cluster ◽  
Diagnostic Methods ◽  
Diagnosis And Treatment ◽  
Syndrome Differentiation ◽  
The Novel ◽  
Sample Data

Abstract Background: Insomnia as one of the dominant diseases of traditional Chinese medicine (TCM) has been extensively studied in recent years. To explore the novel approaches of research on TCM diagnosis and treatment, this paper presents a strategy for the research of insomnia based on machine learning. Methods: First of all, 654 insomnia cases have been collected from an experienced doctor of TCM as sample data. Secondly, in the light of the characteristics of TCM diagnosis and treatment, the contents of research samples have been divided into four parts: the basic information, the four diagnostic methods, the treatment based on syndrome differentiation and the main prescription. And then, these four parts have been analyzed by three analysis methods, including frequency analysis, association rules and hierarchical cluster analysis. Finally, a comprehensive study of the whole four parts has been conducted by random forest. Results: Researches of the above four parts revealed some essential connections. Simultaneously, based on the algorithm model established by the random forest, the accuracy of predicting the main prescription by the combinations of the four diagnostic methods and the treatment based on syndrome differentiation was 0.85. Furthermore, having been extracted features through applying the random forest, the syndrome differentiation of five zang-organs was proven to be the most significant parameter of the TCM diagnosis and treatment.Conclusions: The results indicate that the machine learning methods are worthy of being adopted to study the dominant diseases of TCM for exploring the crucial rules of the diagnosis and treatment.

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