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External Association Analysis of Famous Doctors' Dysmenorrhea Medical Cases Based on Data Mining
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作者 LIU Li-jia ZHU Yao +3 位作者 LU Ming YANG Tao HAN Wei-guo ZHANG Xiao-yun 《World Journal of Integrated Traditional and Western Medicine》 2022年第1期34-42,共9页
Objective:Dysmenorrhea is a common gynecological disease.Some severe symptoms affect the quality of life,causing physical and psychological discomfort.To analyze the dysmenorrhea cases of famous Senior traditional Chi... Objective:Dysmenorrhea is a common gynecological disease.Some severe symptoms affect the quality of life,causing physical and psychological discomfort.To analyze the dysmenorrhea cases of famous Senior traditional Chinese medicine(TCM)doctors and TCM masters through the data mining technology and explore core related rules between the symptoms,pathogenesis,coated tongue,pulse condition,so as to deeply deconstruct the law of TCM clinical differentiation and treatment of dysmenorrhea,verify the effectiveness of the law,and optimize the clinical TCM diagnosis and treatment scheme.Methods:The external correlation analysis of dysmenorrhea medical cases through the Medcase data processing platform and the algorithm of FP-Growth enhanced association analysis was applied.Results:Altogether 171 medical records were studied,which included 171 female patients and 483 clinical visits.The age of the oldest patient was 49,the age of the youngest was 14,the average age was 28 years old.The medical cases involoved 41 kinds of pathogenesis,147 clinical symptoms,16 types of pulse condition,84 types of coated tongue and 292 traditional Chinese medicine.The external correlation processing revealed that there were 25 groups of clinical symptoms and TCM association rules;17 groups of clinical symptoms and secondary TCM association rules;21 groups of pathogenesis and Chinese medicine association rules;34 rules of coated tongue and Chinese medicine association rules;19 rules of pulse condition and Chinese medicine association rules;28 rules of clinical symptoms and pathogenesis associations.Conclusion:When treating dysmenorrhea according to the differentiation and treatment of TCM,the viscera location of the core pathogenesis mainly are kidney,spleen and liver,the pathological factors focus on blood deficiency,blood stasis and qi stagnation.The highly-related TCM include Danggui(Radix Angelicae Sinensis),Baishao(Radix Paeoniae Alba),Chuanxiong(Rhizoma Ligustici),Yanhusuo(Rhizoma Corydalis),Xiangfu(Rhizoma Cyperi).The study of these rules has reference value for the acquisition of the core pathogenesis,the clinical differentiation and the medication. 展开更多
关键词 DYSMENORRHEA Traditional Chinese medicine Medical case Data mining External association
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Intra-set correlation analysis of medical records of thyroid cancer treated by traditional Chinese medicine Master ZHOU Zhongying
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作者 XU Ziyuan ZHU Yao +1 位作者 LU Ming ZHOU Zhongying 《Digital Chinese Medicine》 2022年第2期141-153,共13页
Objective Based on intra-set correlation analysis, this paper deconstructs the clinical medical records of traditional Chinese medicine(TCM) Master ZHOU Zhongying in treating thyroid cancer, and analyzes the experienc... Objective Based on intra-set correlation analysis, this paper deconstructs the clinical medical records of traditional Chinese medicine(TCM) Master ZHOU Zhongying in treating thyroid cancer, and analyzes the experience in “mechanism-syndrome-medicine-prescription” for thyroid cancer.Methods Through Medcase data processing platform, based on Frequent Pattern(FP)-Growth enhanced correlation analysis algorithm, the medical records of Professor ZHOU Zhongying for the treatment of thyroid cancer from June 1, 2001 to February 28, 2015 were analyzed within the set.Results This study involved 43 medical records, 43 patients, and 167 visits. After processing intra-set correlations, 28 groups of highly correlated symptoms, 21 groups of highly correlated tongue images, 10 groups of highly correlated pulse conditions, 28 groups of highly correlated pathogenesis, 34 groups of highly correlated herbs, and 26 groups of highly correlated western medicine diagnosis were selected. Professor ZHOU Zhongying treats thyroid cancer according to syndrome differentiation. Symptoms with more association rules included neck swelling, neck pain, cough, and dry mouth;tongue images with more association rules included dark purple tongue, dark red tongue, and fissured tongue;pulse conditions with more association rules were wiry pulse, thready pulse, small pulse, and slippery pulse;the pathogenesis with more association rules was phlegm and blood stasis, damp-heat accumulation,and impairment of both Qi and Yin;herbs with more association rules were Chaihu(Bupleuri Radix), Zeqi(Sun Euphoribiae Herb), and Tiandong(Asparagi Radix);western medicine diagnosis with more association rules included thyroid cancer, insomnia, and chronic gastritis.Conclusion Thyroid cancer mostly presents as deficiency in origin and excess in manifestations. The basic pathogenesis is phlegm and blood stasis, damp-heat accumulation, and impairment of both Qi and Yin, which are closely related to liver, kidney, and spleen. Professor ZHOU Zhongying adopts both attack and supplement approaches as the general treatment principle, with a strong emphasis on regulating Qi and relieving depression, eliminating phlegm and resolving stagnation, eliminating dampness and turbidity, clearing fire and destroying poison, moistening dryness and softening hard mass, invigorating Qi and nourishing Yin, and paying attention to nourishing liver and kidney, invigorating spleen and stomach,while protecting the heart and lungs. 展开更多
关键词 Traditional Chinese medicine Master ZHOU Zhongying Thyroid cancer Empirical analysis Data mining Intra-set association Phlegm and blood stasis Damp-heat accumulation Combination of attack and supplement
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Environmental Drivers and Spatial Prediction of the Critically Endangered Species Thuja sutchuenensis in Sichuan-Chongqing,China
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作者 Liang Xie Peihao Peng +1 位作者 Haijun Wang Shengbin Chen 《Phyton-International Journal of Experimental Botany》 SCIE 2022年第9期2069-2086,共18页
Identifying the ecological environment suitable for the growth of Thuja sutchuenensis and predicting other potential distribution areas are essential to protect this endangered species. After selecting 24 environmenta... Identifying the ecological environment suitable for the growth of Thuja sutchuenensis and predicting other potential distribution areas are essential to protect this endangered species. After selecting 24 environmental factors thatcould affect the distribution of T. sutchuenensis, including climate, topography, soil and Normalized DifferenceVegetation Index (NDVI), we adopted the Random Forest-MaxEnt integrated model to analyze our data. Basedon the Random Forest study, the contribution of the mean temperature of the warmest quarter, mean temperatureof the coldest quarter, annual mean temperature and mean temperature of the driest quarter was large. Based onMaxEnt model prediction outputs, the potential distribution map not only identified areas that originallyrecorded T. sutchuenensis, such as Xuanhan County, Kai County and Chengkou County, but also identified highlysuitable distribution areas where T. sutchuenensis may exist, including Wanyuan County, Sichuan Province, andthe junction of Chongqing and Hubei Province. This provides a more explicit geographic range for ex situ conservation and reintroduction of T. sutchuenensis. Our results also indicate that, in addition to climate factors,topography and soil factors are also important environmental factors that affect distribution. This provides a theoretical basis for subsequent laboratory construction to simulate the indoor growth of T. sutchuenensis. 展开更多
关键词 Thuja sutchuenensis environmental drivers spatial prediction CONSERVATION Random Forest-MaxEnt model
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Metal Corrosion Rate Prediction of Small Samples Using an Ensemble Technique
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作者 Yang Yang Pengfei Zheng +3 位作者 Fanru Zeng Peng Xin Guoxi He Kexi Liao 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第1期267-291,共25页
Accurate prediction of the internal corrosion rates of oil and gas pipelines could be an effective way to prevent pipeline leaks.In this study,a proposed framework for predicting corrosion rates under a small sample o... Accurate prediction of the internal corrosion rates of oil and gas pipelines could be an effective way to prevent pipeline leaks.In this study,a proposed framework for predicting corrosion rates under a small sample of metal corrosion data in the laboratory was developed to provide a new perspective on how to solve the problem of pipeline corrosion under the condition of insufficient real samples.This approach employed the bagging algorithm to construct a strong learner by integrating several KNN learners.A total of 99 data were collected and split into training and test set with a 9:1 ratio.The training set was used to obtain the best hyperparameters by 10-fold cross-validation and grid search,and the test set was used to determine the performance of the model.The results showed that theMean Absolute Error(MAE)of this framework is 28.06%of the traditional model and outperforms other ensemblemethods.Therefore,the proposed framework is suitable formetal corrosion prediction under small sample conditions. 展开更多
关键词 Oil pipeline BAGGING KNN ensemble learning small sample size
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