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Objective: To fulfill the TCM (traditional Chinese medicine) health management needs of female through constructing the intervention knowledge base, explore the long-term development mechanism of intervention knowledge base. Methods: The structure of female TCM Health Intervention Knowledge was designed base according to the characteristics of TCM health status of females. The inferential mechanism by studying the relation between the female health status and the diet therapy scheme was explored based on syndrome differentiation. A Long-term development mechanism of TCM health intervention knowledge database was designed based on big data and effect feedback mechanism. Results: The classification standard of the TCM Health Intervention Knowledge base of female includes the state of the viscera functions, qi and blood, yin and yang, and pathogenic properties of the body under the illness and health condition. The dietary therapy formula inference engine can provide food material according to the region, natures, function of tonifying, evil eliminating, to match the female health status, and constantly adjusting and improving the Intervention plan according to the feedback. Conclusion: The study proves the construction plan of TCM Health Intervention Knowledge base of female is able to meet the needs of female TCM health management intervention, and the method of constantly adjusting and improving the intervention plan according to the feedback helps to realize the precise recommendation and long-term development of intervention knowledge base.
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Objective: To explore pulse characteristic of the health female college students and their relationship with menstrual cycle. Methods: The subjects were 17 female college students of Jiangxi University of Traditional Chinese Medicine. Pulse test was performed with pulse bracelet. The detection time was every day in the wake and has not yet get up and wake up at any time before going to bed with a pulse-taking bracelet, and recorded the current menstrual cycle information. The pulses of the wake that has not yet get up and wake up at any time before going to bed took consistency analysis of the record with Kruskal Wallis Test. The pulse of menstruation stage analysis was compared with chi-square test. Results: The pulses of the wake that has not yet get up and wake up at any time before going to bed consistency was poor except rapid pulse (P＞ 0.05) . The occurrence frequency of slippery pulse and string-like pulse were 55.21％ and26. 03％ respectively. The pulses of premenstrual period, post menstrual period and menstrual period were not much different from others. The occurrence frequency of moderate pulse, string-like pulse, unsmooth pulse, slippery pulse in intermenstrual period respectively were 40.68％, 44.07％, 30.51％, and 40.68％. The occurrence frequency of moderate pulse, string-like pulse, unsmooth pulse, slippery pulse in-non intermenstrual period respectively were 17.38％, 24.69％, 10.45％, 56.30％. The difference was significant (P ＜ 0.05) . Conclusion: The female college students are mainly in terms of slippery pulse. The occurrence frequency slippery pulse in intermenstrual period respectively are less common. The string-like pulse, moderate pulse, unsmooth pulse in intermenstrual period are more common than in-non intermenstrual period.
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Objective: To construct the evaluation index of follow-up assessments on TCM (traditional Chinese medicine) health management of female. Methods: The evaluation indicators and score criteria were extracted for the efficacy evaluation of diseases and syndromes related to irregular menstruation in The criteria of diagnosis and therapeutic effect of diseases and syndromes in Traditional Chinese Medicine and Guidelines of clinical research of new drugs of Traditional Chinese Medicine; The health behaviors related to the onset of irregular menstruation diseases, such as diet, emotion, exercise, etc. were collected to build index of health behavior of irregular menstruation. Results: A comprehensive index system of follow-up assessments on TCM health management of female composed of disease curative effect, syndrome curative effect and health behavior score was constructed. Conclusion: The evaluation index system helps to dynamically track the effectiveness of interventions and management, and helps users to adjust the intervention plan and avoid the unhealthy behaviors.
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Objective: To analyze the characteristics of the healthy state of TCM (Traditional Chinese Medicine) of female, and preliminarily constructs the model of TCM health status identification of female with menstrual cycle. Methods: The text of disease diagnosis and syndrome differentiation of menstrual-cycle-linked disorders from Guidelines for diagnosis and treatment of common disease of gynecology in Traditional Chinese Medicine was analyzed, and the symptoms related with viscera functions, the waxing and waning of qi and blood, and pathogenic properties were extracted. The questionnaires of diseases and syndrome elements differentiation of female by calculating the weight relationship between symptoms and health status were designed to estimate the interior state of waxing and waning of yin-yang by figuring out the different periods of menstrual, and in the last step, Constitution in Chinese medicine Questionnaire was used to identify the constitution. Through the above four identification methods, a comprehensive identification of the female's health status of TCM was formed. Results: Through the disease identification model, we distinguished the state of disease and yet disease. And through the syndrome elements differentiation model, we knew the viscera functions, the waxing and waning of qi-blood and yin-yang, and pathogenic properties. And by identifying the internal qi-blood and yin-yang status, we initially built the model that can identify health status of female integrally with the constitution. Conclusion:The model identification results can reflect the comprehensive health status of female in multiple dimensions. It can make a fine classification of women.s TCM health status. It can not only help to know the previous health status but also help to speculate the future health trend, which contributes to the formulation of personalized health interventions of follow-up.
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OBJECTIVE: To analyze the indications of the therapies for rheumatoid arthritis (RA) with neural network model analysis. METHODS: Three hundred and ninety-seven patients were included in the clinical trial from 9 clinical centers. They were randomly divided into Western medicine (WM) treated group, 194 cases; and traditional Chinese herbal medicine (CM) treated group, 203 cases. A complete physical examination and 18 common clinical manifestations were prepared before the randomization and after the treatment. The WM therapy included voltaren extended action tablet, methotrexate and sulfasalazine. The CM therapy included Glucosidorum Tripterygii Totorum Tablet and syndrome differentiation treatment. The American College of Rheumatology 20 (ACR20) was taken as efficacy evaluation. All data were analyzed on SAS 8.2 statistical package. The relationships between each variable and efficacy were analyzed, and the variables with P<0.2 were included for the data mining analysis with neural network model. All data were classified into training set (75%) and verification set (25%) for further verification on the data-mining model. RESULTS: Eighteen variables in CM and 24 variables in WM were included in the data-mining model. In CM, morning stiffness, swollen joint number, peripheral immunoglobulin M (IgM) level, tenderness joint number, tenderness, rheumatoid factor (RF), C-reactive protein (CRP) and joint pain were positively related to the efficacy, and disease duration and more urination at night negatively related to the efficacy. In WM, erythrocyte sedimentation rate (ESR), weak waist, white fur in tongue, joint pain, joint stiffness and swollen joint were positively related to the efficacy, and yellow fur in tongue, red tongue, white blood negatively related to the efficacy. In the analysis with the neural network model in the patients of verification set, the predictive response rates of 20% patients would be 100% and 90% in the treatment with CM and WM, respectively. CONCLUSION: Neural network model analysis, based on the full clinical trial data with collection of both traditional Chinese medicine and modern medicine diagnostic information, shows a good predictive role for the information in the efficacy in rheumatoid arthritis.
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Objective: To observe the effects of Small Qinglong Decoction medicine-containing serum on ASMC proliferation action induced by ET-1.Methods: There were six groups in the experiment: normal group(10% normal control serum),model group(ET-1 added 10% normal control serum),Small Qinglong Decoction high dose group(ET-1 added 10% Small Qinglong Decoction high dose serum),Small Qinglong Decoction middle dose group(ET-1 added 10% Small Qinglong Decoction middle dose serum),Small Qinglong Decoction low dose group(ET-1 added 10% Small Qinglong Decoction low dose serum) and Dexamethasone group(ET-1 added 10% Dexamethasone serum),eight slots every group.ASMC proliferation status of 24h,48h and 72h were detected with MTT chromometry.Results: Compared with model group,ASMC proliferation in Small Qinglong Decoction low dose group medicine-containing serum each stage and middle dose group24h and 72h all had significant difference(P