Traditional Chinese Medicine Doctors Research Articles

PresRecST: a novel herbal prescription recommendation algorithm for real-world patients with integration of syndrome differentiation and treatment planning.

Herbal prescription recommendation (HPR) is a hot topic and challenging issue in field of clinical decision support of traditional Chinese medicine (TCM). However, almost all previous HPR methods have not adhered to the clinical principles of syndrome differentiation and treatment planning of TCM, which has resulted in suboptimal performance and difficulties in application to real-world clinical scenarios. We emphasize the synergy among diagnosis and treatment procedure in real-world TCM clinical settings to propose the PresRecST model, which effectively combines the key components of symptom collection, syndrome differentiation, treatment method determination, and herb recommendation. This model integrates a self-curated TCM knowledge graph to learn the high-quality representations of TCM biomedical entities and performs 3 stages of clinical predictions to meet the principle of systematic sequential procedure of TCM decision making. To address the limitations of previous datasets, we constructed the TCM-Lung dataset, which is suitable for the simultaneous training of the syndrome differentiation, treatment method determination, and herb recommendation. Overall experimental results on 2 datasets demonstrate that the proposed PresRecST outperforms the state-of-the-art algorithm by significant improvements (eg, improvements of P@5 by 4.70%, P@10 by 5.37%, P@20 by 3.08% compared with the best baseline). The workflow of PresRecST effectively integrates the embedding vectors of the knowledge graph for progressive recommendation tasks, and it closely aligns with the actual diagnostic and treatment procedures followed by TCM doctors. A series of ablation experiments and case study show the availability and interpretability of PresRecST, indicating the proposed PresRecST can be beneficial for assisting the diagnosis and treatment in real-world TCM clinical settings. Our technology can be applied in a progressive recommendation scenario, providing recommendations for related items in a progressive manner, which can assist in providing more reliable diagnoses and herbal therapies for TCM clinical task.

Images of Traditional Chinese Medicine Doctors in Chinese Literature

Since ancient times, doctors have usually played the image of rescuers who save lives. As a symbol-rich image, "doctor" often enters the scope of writers' creativity and becomes a typical creative theme. This paper explores the image of Traditional Chinese Medicine (TCM) doctors in literature. The purpose of the study is to understand how TCM practitioners are portrayed and represented in literature, to analyze their social and cultural influence and their impact on people's perceptions and attitudes towards TCM. The relevance of this article is that it can help people to better understand the position and image of TCM in different historical periods and cultural environments, as well as its relationship with society, culture and people's lives. The subject of this paper is the image of TCM doctors in literary works of a certain period, region or cultural context such as ancient works, modern literary works and works of specific writers. By analyzing the images in different works, the diversity of such images of TCM physicians such as wise doctors and mysterious healers can be demonstrated. This paper uses methods of literary analysis, including close reading of the text, character analysis, plot and theme study. The text is also studied in the context of historical and cultural context to understand the views and attitudes of the society of the time towards TCM and doctors. The scientific novelty of studying the image of traditional Chinese medicine in Chinese literature gives us an interdisciplinary perspective that integrates literature with medicine and cultural studies and offers new ways to deeply understand TCM culture and human perception of health. The results of the study indicate the diversity of TCM physicians' images in the literature. In addition, the findings may reflect different understandings and evaluations of TCM in different periods and cultural contexts.

Opportunities and challenges of traditional Chinese medicine doctors in the era of artificial intelligence.

With the exponential advancement of artificial intelligence (AI) technology, the realm of medicine is experiencing a paradigm shift, engendering a multitude of prospects and trials for healthcare practitioners, encompassing those devoted to the practice of traditional Chinese medicine (TCM). This study explores the evolving landscape for TCM practitioners in the AI era, emphasizing that while AI can be helpful, it cannot replace the role of TCM practitioners. It is paramount to underscore the intrinsic worth of human expertise, accentuating that artificial intelligence (AI) is merely an instrument. On the one hand, AI-enabled tools like intelligent symptom checkers, diagnostic assistance systems, and personalized treatment plans can augment TCM practitioners' expertise and capacity, improving diagnosis accuracy and treatment efficacy. AI-empowered collaborations between Western medicine and TCM can strengthen holistic care. On the other hand, AI may disrupt conventional TCM workflow and doctor-patient relationships. Maintaining the humanistic spirit of TCM while embracing AI requires upholding professional ethics and establishing appropriate regulations. To leverage AI while retaining the essence of TCM, practitioners need to hone holistic analytical skills and see AI as complementary. By highlighting promising applications and potential risks of AI in TCM, this study provides strategic insights for stakeholders to promote the integrated development of AI and TCM for better patient outcomes. With proper implementation, AI can become a valuable assistant for TCM practitioners to elevate healthcare quality.

Objective Evaluation of Pulse Width Using an Array Pulse Diagram.

Pulse width, which can reflect qi, blood excess, and deficiency, has been used for diagnosing diseases and determining the prognosis in traditional Chinese medicine (TCM). This study aimed to devise an objective method to measure the pulse width based on an array pulse diagram for objective diagnosis. The channel 6, the region wherein the pulse wave signal is the strongest, is located in the middle of the pulse sensor array and at the guan position of cunkou during data collection. Therefore, the main wave (h1) time of the pulse wave was collected from the channel 6 through calculation. The left h1 time was collected from the remaining 11 channels. The amplitudes at these time points were extracted as the h1 amplitudes for each channel. However, the pulse width could not be calculated accurately at 12 points. Consequently, a bioharmonic spline interpolation algorithm was used to interpolate the h1 amplitude data obtained from the horizontal and vertical points, yielding 651 (31 × 21) h1 amplitude data. The 651 data points were converted into a heat map to intuitively calculate the pulse width. The pulse width was calculated by multiplying the number of grids on the vertical axis with the unit length of the grid. The pulse width was determined by TCM doctors to verify the pulse width measurement accuracy. Meanwhile, a color Doppler ultrasound examination of the volunteers' radial arteries was performed and the intravascular meridian widths of the radial artery compared with the calculated pulse widths to determine the reliability. The pulse width determined using the maximal h1 amplitude method was comparable with the radial artery intravascular meridian widths measured using color Doppler ultrasound. The h1 amplitude was higher in the high blood pressure group and the pulse width was greater. The pulse width determined using the maximal h1 amplitude was objective and accurate. Comparison between the pulse widths of the normal and high blood pressure groups verified the reliability of the method.

TLDA: A transfer learning based dual-augmentation strategy for traditional Chinese Medicine syndrome differentiation in rare disease

The Traditional Chinese Medicine (TCM) has demonstrated its significant medical value over the decades, particularly during the COVID-19 pandemic. TCM-AI interdisciplinary models have been proposed to model TCM knowledge, diagnosis, and treatment experiments in clinical practice. Among them, numerous models have been developed to simulate the syndrome differentiation process of human TCM doctors for automatic syndrome diagnosis. However, these models are designed for normal scenarios and trained using a supervised learning paradigm which needs tens of thousands of training samples. They fail to effectively differentiate syndromes in rare disease scenarios where the available TCM electronic medical records (EMRs) are very limited for each unique syndrome. To address the challenge of rare diseases, this study proposes a simple yet effective method called Transfer Learning based Dual-Augmentation (TLDA). TLDA aims to augment the limited EMRs at both the sample-level and feature-level, enriching the pathological and medical information during training. Extended experiments involving 11 comparison models, including the state-of-the-art model, demonstrate the effectiveness of TLDA. TLDA outperforms all comparison models by a significant margin. Furthermore, TLDA can also be extended to other medical tasks when the EMRs for diagnosis are limited in samples.

Analysis of the cluster efficacy and prescription characteristics of traditional Chinese medicine intervention for non-small cell lung cancer based on a clustering algorithm.

In recent years, malignant tumors have gradually become one of the main causes of death for Chinese residents, of which lung cancer ranks first in both the incidence and mortality in China. To mine the text of traditional Chinese medicine (TCM) clinical medical cases after data cleaning, analyze it, and study the experience of TCM doctors in treating non-small cell lung cancer (NSCLC). The applied approach was based on the data mining methods of decentralized and hierarchical system clustering of data from a drug and prescription database. This study involved 215 patients, 287 cases, and 147 types of clinical drugs. The data analysis of the clinical treatment of NSCLC in TCM showed that Erchen Decoction was the main method for the treatment of non-small cell lung cancer in clinical treatment of non-small cell lung cancer. Junjian recipes were close to each other, with Banzhilian, Lobelia, Shanci Mushroom, Hedyotis diffusa to anticancer and detoxify. This study analyzed the core TCM prescription for NSCLC by collecting the empirical essence and characteristics of specific medications. It has some guiding scientific significance for the clinical treatment of lung cancer.

Dr. Lian Zhu: A Founder of Contemporary Acupuncture Medicine.

As an inseparable part of Traditional Chinese Medicine (TCM), acupuncture has been used in more than 196 countries or regions and has played an increasingly important role in health care. This article introduces Dr. Lian Zhu, MD, who made great contributions to acupuncture development. Dr. Zhu was a medical doctor, a military physician in her early life, and a high-ranking officer in the health care system of the Chinese government. She became famous as an acupuncturist after learning acupuncture in 1945. She was highly influenced by Zhijun Lu, MD, who learned acupuncture from Zuotian Ren, a TCM doctor in Yan'an, who had cured Chairman Mao Zedong's intractable shoulder pain. Dr. Zhu was one of the 2 earliest acupuncture trainers in the Chinese military health system, helping the Chinese communist military overcome resource shortages during the Chinese Civil War. She was one of China's most-influential acupuncture educators, having taught many acupuncture classes that trained many acupuncturists from 1945 to 1955. She was also an officer and policy maker in the Health Department of the central government, where she established such policy initiatives as training content for TCM doctors' reeducation schools. Dr. Zhu was ones of the earliest acupuncture researchers and administrators with a government-endorsed background. She created the first public acupuncture university in history in 1976 as well as 2 key acupuncture institutes in China and was director of both. She played a crucial role in promoting acupuncture research through TCM and biomedical methods, and was the first scholar in China to publish a thorough book on medical acupuncture using Western-biomedical language, which was highly praised by Chairman Mao. Dr. Zhu's acupuncture theory objectively promoted acceptance of medical acupuncture by the general public, medical doctors, government officials, and international medical societies.

Applying a co‐design approach with key stakeholders to design interventions to reduce illegal wildlife consumption

Abstract Co‐design, an approach that seeks to incorporate the experiences and perspectives of different stakeholders, is increasingly being used to develop audience‐oriented behaviour change interventions. The complexity of wildlife consumption behaviour makes the co‐design approach an important potential tool for the design of conservation interventions that aim to reduce illegal wildlife trade. Yet, little is known about how to adapt and apply the co‐design approach to the wildlife trade sector. Here, we applied a co‐design approach to develop interventions aimed at reducing illegal animal‐based medicine consumption in China. We conducted three workshops with key stakeholders: consumers of animal‐based medicines, pharmacy workers who sell them and traditional Chinese medicine (TCM) doctors who prescribe them. We then developed a theory of change to ensure the relevance of the co‐designed intervention prototypes. Our co‐design process identified five main pathways of interventions, including two inclusive solutions that may have been previously overlooked in behaviour change work in this context. These were an intervention to promote the appropriate use of TCM and one to increase consumers' capacity to identify the legality of products. Our prototype interventions also enhanced existing views related to the role of medical practitioners in health‐risk communication. We used our co‐design process and reflections on its application to this specific market to provide guidelines for future conservation program planning in the broader wildlife trade context. Some intervention prototypes produced during co‐design may need wider stakeholder involvement to increase their feasibility for implementation. We show that the co‐design process can integrate multiple stakeholders' perspectives in the ideation stage, and has the potential to produce inclusive intervention designs that could drive innovation in conservation efforts to reduce illegal consumption of a range of wild species. Read the free Plain Language Summary for this article on the Journal blog.

Pulse Wave Measuring Sensor System via the Average Magnitude Difference Function Entropy for Classifying Cardiac Conditions

The formation and changes of the pulse wave are affected by the functional status of the heart, blood, and arterial vessels. The pulse signal covers pathological information in the cardiovascular system, and the doctor of traditional Chinese medicine (TCM) can diagnose diseases by feeling the pulse. The diagnosis of diseases through feeling the pulse of TCM primarily relies on the doctor’s feelings and subjective experience, and it lacks objectified data. In this work, pulse signals were collected digitally by designing pulse sensors and pulse acquisition systems in accordance with the feel pulse habits of TCM. The pulse rate variability was used to characterize the functional state of the heart. The average magnitude difference function (AMDF) fuzzy entropy method was proposed to investigate the change in pulse rate. A total of 77 volunteers with different heart health conditions were recruited for the collection of the pulse signal. Results showed that the AMDF fuzzy entropy can distinguish clearly among knotted pulse, regular intermittent pulse, and normal pulse. Therefore, this method has potential application value to realize cardiac-function state analysis and abnormal recognition.

Zhang Zhongjing Cultural Brand Construction from the Perspective of Traditional Chinese Medicine Culture and Wellness Tourism

AbstractNowadays, traditional Chinese medicine (TCM) culture and wellness tourism are developing toward integration with an inherent and inevitable basis. A new business mode of TCM wellness tourism bred has emerged, injecting new vitality into the development of TCM culture and innovation of tourism. As the cultural representative of TCM industry, Zhang Zhongjing culture should seize the opportunity to make a breakthrough in its brand construction with the help of wellness tourism. The main construction strategies include actively launching books or films and television dramas based on the deeds of Zhang Zhongjing and other famous TCM doctors, turning herbs cultivation bases into special tourism and sightseeing parks, establishing research and dissemination bases of TCM culture, and building TCM wellness tourism bases that integrate learning, rehabilitation, and tourism, using information technology and cultural media platforms to introduce Zhang Zhongjing culture to the world.

TCM disease diagnosis based on convolutional cyclic neural network algorithm

The unique diagnosis and treatment mode of traditional Chinese medicine provides a lot of diagnostic basis with reference value for modern medicine, which is welcomed by people all over the world and has attracted extensive attention of medical researchers. However, the unique diagnosis and treatment method of traditional Chinese medicine also brings difficulties to the dissemination of traditional Chinese medicine. The diagnosis method of traditional Chinese medicine is difficult to objectively and quantitatively express, and the diagnosis process is also closely related to the subjective experience of traditional Chinese medicine doctors. , lacking established standards. In view of the above-mentioned difficulties in the modernization of traditional Chinese medicine, the development of modern information science and technology has brought a turning point to the intelligentization of disease differentiation in traditional Chinese medicine. The core of traditional Chinese medicine diagnosis and treatment is diagnosis and classification. How to convert the difficult to describe disease diagnosis and treatment process of traditional Chinese medicine into language that can be distinguished and understood by ordinary doctors, and build an auxiliary diagnosis and treatment model to provide reference for Chinese doctors to see a doctor is the main problem to be solved in this paper.

The linkage of gut microbiota and the property theory of traditional Chinese medicine (TCM): Cold-natured and sweet-flavored TCMs as an example.

The property theory of traditional Chinese medicine (TCM) is a unique medical theory based on an extensive clinical practice for thousands of years, which guides TCM doctors choosing proper medicines to treat specific diseases. The nature and flavor of TCM are a high generalization of drug's characteristics according to the property theory. Despite intensive investigations, the modern interpretation of TCM property theory still confronts several challenges, which greatly hampers the elucidation of TCM's mechanisms as well as its application. Compelling evidence has proved that gut microbiota may be a potential indicator for TCM's efficacy and mechanism. Nevertheless, at present, the relationship between the gut microbiota and the nature and flavor of TCM has not been fully elucidated. To fill the gap in this field, we developed a comprehensive study to investigate the relationship between gut microbial community and TCM's property. We searched "PubMed" and "China National Knowledge Infrastructure (CNKI)" with the key word "gut microbiota", and screened the published articles related to TCM. In this review, we mainly applied cold-natured and sweet-flavored TCMs as an example to explore the modulation of cold-natured and sweet-flavored TCMs on gut microbiota, and identify the potential relationship between the alterations of gut microbiota and TCM's efficacy. We found cold-natured and sweet-flavored TCMs possess several pharmacological activities and generally enrich beneficial bacteria like Akkermansia, Bacteroides, Lactobacillus and Bifidobacterium, which is in good accordance with their pharmacological effects. Simultaneously, these TCMs reduce the relative abundance of some harmful bacteria belonging to Firmicutes (Streptpcoccus, Enterococcus, Turicibacter, Anaerostipes and Oscillibacter) and Proteobacteria (Helicobacter, Enterobacter, Sutterella, Klebsiella, Desulfovibrio, Escherichia coli and Campylobacter jejuni). These results indicate that there are some intrinsic correlations between gut microbiota and the property of TCM, and gut microbiota may serve as a potential indicator to reflect the property of TCM. This pilot but comprehensive review provides an interesting proposal that the ancient theory of TCM property may be interpreted by the modern biological findings in gut microbiome.

Prevalence and risk factors of atopic dermatitis in Chinese adults: a nationwide population-based cross-sectional study.

Prevalence and risk factors of atopic dermatitis in Chinese adults: a nationwide population-based cross-sectional study.

Chemopreventive effects of Xiang Sha Liu Jun Zi Tang on paclitaxel-induced leucopenia and neuropathy in animals.

Paclitaxel frequently induces peripheral neuropathy and myelosuppression during cancer treatment. According to the National Health Insurance Research Database of Taiwan, traditional Chinese medicine doctors widely use Xiang Sha Liu Jun Zi Tang (XSLJZT) to treat breast cancer patients who have received paclitaxel. We explored the combined therapeutic effects of XSLZJT with paclitaxel. XSLJZT did not exhibit significant cytotoxic effects on P388-D1 cells; however, the combination of XSLJZT (100 and 500mg/kg) with paclitaxel prolonged the survival rate in P388-D1 tumor-bearing mice compared to paclitaxel-only. In addition, XSLJZT was found to enhance white blood cells (WBC) counts and promote leukocyte rebound in paclitaxel-induced leukopenia in mice. XSLJZT also reduced paclitaxel-induced mechanical pain and inhibited c-Fos protein expression in the L4-6 spinal cords of Wistar rats. Moreover, paclitaxel-induced shortening of the nerve fibers of dorsal root ganglion cells was ameliorated by pre-treatment with XSLJZT. Therefore, we suggest that XSLJZT could be used as an adjunct for cancer patients, as the formula could decrease paclitaxel-induced neuropathy and myelosuppression.

Research Progress in Diagnosis and Treatment of Postpartum Depression by Traditional Chinese Medicine

In this paper, by analyzing a large number of domestic and foreign literatures on the treatment of postpartum depression in recent years, the research progress of traditional Chinese medicine (TCM) in the treatment of postpartum depression was systematically reviewed. Sum up after a postpartum depression of the most common etiology and pathogenesis, from the compound Chinese medicine, acupuncture, needle medicine use, massage, music therapy and traditional Chinese medicine fumigation treatment, according to the basic theory of TCM in detail its historical source, choose party on the basis of TCM syndrome differentiation, acupuncture and moxibustion therapy in a variety of acupuncture and moxibustion treatment of forms, and other characteristics of traditional Chinese medicine therapy. Literature review shows that: The doctor of traditional Chinese medicine in the treatment of postpartum depression, with overall concept as guiding ideology, thus improve the systemic symptom of patients, improve the quality of life, and there are diversified TCM therapies, patients and their families have high acceptance, small side effects, make up the deficiency of western medicine, not only in the clinical practice to improve the curative effect of treatment of postpartum depression, also for the general medical compatriots to broaden the diagnosis and treatment method of postpartum depression, provide evidence for the selection of treatment for such patients.

The intelligent experience inheritance system for Traditional Chinese Medicine.

The inheritance of knowledge and experience was crucial to the development of Traditional Chinese Medicine (TCM). However, the existing methods of inheriting the unique clinical experience of famous veteran TCM doctors still followed the outdated and inefficient Master-Prentice schema. In addition, the inherited medical books and records were usually lack of standardization and systematization. In this article, a new method for inheriting the academic thoughts and clinical experience of famous veteran doctors with the help of artificial intelligence technology was explored. Due to the individualized treatment characteristics namely "same disease with different treatments, different diseases with the same treatment," the intelligent inheritance of TCM faced many technical barriers. To tackle these problems, we proposed a prototype system framework for the intelligent inheritance of famous veteran doctors based on rules and deep learning models and performed a case study on the treatment of pediatric asthma. The architecture could not only make full use of the advantages of deep learning, but also integrate the valuable knowledge and experience analysis of famous veteran doctors from injected rules. Specifically, the study took pediatric asthma medical records as training and test samples and calculated the similarity between the generated prescriptions and the real-world clinical prescriptions from the famous veteran doctors. Experimental results showed that the generated prescription could achieve a similarity of more than 90%. It proved that the proposed framework provided a feasible way for the intelligent inheritance and research of the academic thoughts and clinical experience of famous veteran TCM doctors.

Investigating the factors affecting the competence of a traditional Chinese medicine practitioner using structural equation model.

Compared with other medical sciences, Chinese medicine provides professional advantages in disease prevention and the diagnosis of chronic diseases. The training of Chinese medicine practitioners is worthy of investigation. The present study focused on how structural equation modelling (SEM) can be used to analyze the competencies of traditional Chinese medicine (TCM) practitioners to help training an eligible TCM doctor and select suitable staff for TCM hospital. Before the analysis of competence factors for TCM, we developed the scale, including literature review, expert consultation, item pool for the proposed competency model, pilot test of the item pool, and finalization of the scale items. We analyzed questionnaires from 400 TCM practitioners in Hangzhou, Guangzhou, and Wuhan, and then performed an exploratory factor analysis (EFA) and a confirmatory factor analysis (CFA) to extract the valuable items for TCM practitioners. Finally, SEM was employed to develop a competency structure. A total of 21 items in this study's questionnaire were identified as being closely related to the competencies of TCM practitioners, which were further categorized by principal component analysis into five categories: (I) professional values; (II) basic medical knowledge; (III) communication skills; (IV) clinical skills; and (V) information management. Subsequent analyzes showed that clinical skills were the most important competency metric for TCM practitioners; additionally, the mediating role of basic medical knowledge and communication skills could not be ignored in both theory and practice. This research presents a preliminary methodology for evaluating the competence of TCM practitioners and provides hospitals with criteria theoretical reference for training and finding TCM practitioners.

An Analysis of the Clinical Medication Rules of Traditional Chinese Medicine for Polycystic Ovary Syndrome Based on Data Mining.

The aim of the present study is to investigate the rules and characteristics of the clinical administration of traditional Chinese medicine (TCM) in the treatment of polycystic ovary syndrome (PCOS) using data mining methods. Medical cases of well-known contemporary TCM doctors treating PCOS were collected from the China National Knowledge Infrastructure, Chinese Biomedical Literature Service System, Wanfang, Chinese Scientific Journals Database, and PubMed; the data were then characterized, and a standardized database of medical cases was built. This database was used to (1) count the frequency of syndrome types and the herbs used in medical cases by data mining methods and (2) analyze drug association rules and systematic clustering methods. A total of 330 papers were included, involving 382 patients and a total of 1,427 consultations. The most common syndrome type was kidney deficiency; sputum stasis was the core pathological product and causative factor. A total of 364 herbs were used. Among them, 22 herbs were used >300 times, including Danggui (Angelicae Sinensis Radix), Tusizi (Semen Cuscutae), Fuling (Poria), Xiangfu (Nutgrass Galingale Rhizome), and Baizhu (Atractylodis Macrocephalae Rhizoma). Additionally, 22 binomial associations were obtained from the analysis of association rules; five clustering formulae were obtained via the analysis of high-frequency drug clusters; and 27 core combinations were obtained by k-means clustering of formula. In the treatment of PCOS, TCM is primarily employed as a combination approach involving tonifying the kidneys, strengthening the spleen, eliminating damp and dissolving phlegm, activating blood circulation, and resolving blood stasis. The core prescription is primarily a compound intervention based on the Cangfu Daotan pill, Liuwei Dihuang pill, and Taohong Siwu decoction.

Current Situation, Problems and Countermeasures of Clinical Diagnosis and Treatment of Modern Traditional Chinese Medicine

Traditional Chinese medicine (TCM) was a complete and systematic diagnosis and treatment system, but inheritance and innovation were also needed for TCM for adapting to the continuous development and change of modern society, as well as people's pursuit for high quality healthy life. Yin-yang theory, five elements theory and visceral manifestation theory were the precondition for the diagnosis and treatment of TCM, which were used to perform the systematic and comprehensive syndrome differentiation of disease, thus formulate the treatment principles. However, several severe problems which restricted the application and treatment of disease for TCM. At the theory aspect, the basic knowledge of traditional Chinese medicine was not enough, the overall concept of thinking was lacking or weak, and lacking the mastery of the principal theory of TCM, which limited the diagnosis of disease; the professional division was too meticulous, which caused the doctor of TCM only mastered one subject, which caused the non-precise diagnosis of disease. At the syndrome differentiation aspect, traditional disease information collecting with observation, auscultation and olfaction, inquiry, and pulse feeling and palpation, this process was sloppy or omitted severely, which was also limited to the diagnosis of disease for doctor of TCM with the principal theories; parts of the doctor of TCM performed their diagnosis basing on the checking results of western medicine, but ignored the essence of diagnosis and treatment of TCM. At the aspect of treatment, decoction was commonly used in the treatment of diseases, however, bian, needle, moxibustion and the resting strategy of TCM for treating disease were ignored. The aforementioned factors limited the diagnosis, treatment of TCM, as well as the culture of TCM talents, which restricted the development of TCM. Thus, in this study, we anlyzed the current situation and problems of clinical diagnosis and treatment of TCM, and proposed the appropriate suggestion for the disease diagnose and talent culture of TCM by cooperating the principal theory of TCM. In addition, the usage of syndrome differentiation of disease of TCM with the corporation of checking technology of western medicine for the diagnosis of disease, then chose the suitable treating strategy. This work would provide the referential suggestions for the development of TCM and talent training.

TCM Prescription Generation via Knowledge Source Guidance Network Combined with Herbal Candidate Mechanism.

Traditional Chinese medicine (TCM) prescriptions have made great contributions to the treatment of diseases and health preservation. To alleviate the shortage of TCM resources and improve the professionalism of automatically generated prescriptions, this paper deeply explores the connection between symptoms and herbs through deep learning technology, and realizes the automatic generation of TCM prescriptions. Particularly, this paper considers the significance of referring to similar underlying prescriptions as herbal candidates in the TCM prescribing process. Moreover, this paper incorporates the idea of referring to the potential guidance information of corresponding prescriptions when model extracts symptoms representations. To provide a reference for inexperienced young TCM doctors when they prescribe, this paper proposes a dual-branch guidance strategy combined with candidate attention model (DGSCAM) to automatically generate TCM prescriptions based on symptoms text. The format of the data used this paper is the "symptoms-prescription" data pair. The specific method is as follows. First, DGSCAM realizes the extraction of key information of prescription-guided symptoms through a dual-branch network. Then, herbal candidates in the form of prescriptions that can treat symptoms are proposed in view of the compatibility knowledge of TCM prescriptions. To our knowledge, this is the first attempt to use prescriptions as herbal candidates in the prescription generation process. We conduct extensive experiments on a mixed public and clinical dataset, achieving 37.39% precision, 25.04% recall, and 29.99% F1 score, with an average doctor score of 7.7 out of 10. The experimental results show that our proposed model is valid and can generate more specialized TCM prescriptions than the baseline models. The DGSCAM developed by us has broad application scenarios and greatly promotes the research on intelligent TCM prescribing.