The Chinese Neurology and Psychiatry Association conducted a national field trial of its Chinese Classification and Diagnostic Criteria of Mental Disorders (CCMD-2) involov-ing 26 provinces and municipalities, 80 psyc...The Chinese Neurology and Psychiatry Association conducted a national field trial of its Chinese Classification and Diagnostic Criteria of Mental Disorders (CCMD-2) involov-ing 26 provinces and municipalities, 80 psychiatric institutes, and 224 professionals. The results were as follows: (1)95.2% of researchers considered the comprehensibility of the CCMD-2 diagnstic criteria good. Within the ten major categories, comprehensibility ranged from 85.7% to 100%. (2) Of those surveyed concerning the acceptibility of the CCCMD-2 diagnostic criteria, 85.9% considered them acceptable. In individual classifications, the rate ranged from 74.1% to 95.2%. (3) 1498 cases were tested. The overall applicability rate which indicated the consistency between the CCMD-2 result and the actual clinical diagnoses was found to be 87.6%, (averaging Kappa = 0.82,P<0.01), better than those obtained from non-Chinese systems of diagnosis.展开更多
The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parall...The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parallel naive Bayes algorithm(PNBA)for Chinese text classification based on Spark,a parallel memory computing platform for big data.This algorithm has implemented parallel operation throughout the entire training and prediction process of naive Bayes classifier mainly by adopting the programming model of resilient distributed datasets(RDD).For comparison,a PNBA based on Hadoop is also implemented.The test results show that in the same computing environment and for the same text sets,the Spark PNBA is obviously superior to the Hadoop PNBA in terms of key indicators such as speedup ratio and scalability.Therefore,Spark-based parallel algorithms can better meet the requirement of large-scale Chinese text data mining.展开更多
We explore the techniques of utilizing N gram information to categorize Chinese text documents hierarchically so that the classifier can shake off the burden of large dictionaries and complex segmentation process...We explore the techniques of utilizing N gram information to categorize Chinese text documents hierarchically so that the classifier can shake off the burden of large dictionaries and complex segmentation processing, and subsequently be domain and time independent. A hierarchical Chinese text classifier is implemented. Experimental results show that hierarchically classifying Chinese text documents based N grams can achieve satisfactory performance and outperforms the other traditional Chinese text classifiers.展开更多
With the explosive growth of Internet text information,the task of text classification is more important.As a part of text classification,Chinese news text classification also plays an important role.In public securit...With the explosive growth of Internet text information,the task of text classification is more important.As a part of text classification,Chinese news text classification also plays an important role.In public security work,public opinion news classification is an important topic.Effective and accurate classification of public opinion news is a necessary prerequisite for relevant departments to grasp the situation of public opinion and control the trend of public opinion in time.This paper introduces a combinedconvolutional neural network text classification model based on word2vec and improved TF-IDF:firstly,the word vector is trained through word2vec model,then the weight of each word is calculated by using the improved TFIDF algorithm based on class frequency variance,and the word vector and weight are combined to construct the text vector representation.Finally,the combined-convolutional neural network is used to train and test the Thucnews data set.The results show that the classification effect of this model is better than the traditional Text-RNN model,the traditional Text-CNN model and word2vec-CNN model.The test accuracy is 97.56%,the accuracy rate is 97%,the recall rate is 97%,and the F1-score is 97%.展开更多
Objective:To explore the diagnostic value of traditional Chinese medical(TCM)dialectical classification in Hashimoto's thyroiditis complicated with suspicious nodules.Methods:The clinical data of patients with Has...Objective:To explore the diagnostic value of traditional Chinese medical(TCM)dialectical classification in Hashimoto's thyroiditis complicated with suspicious nodules.Methods:The clinical data of patients with Hashimoto's thyroiditis complicated with thyroid nodules in the Department of Breast and thyroid surgery of Weifang Hospital of traditional Chinese Medicine from January 2018 to December 2019 were collected.The patients were examined by 2 or more experienced TCM doctors,and the four diagnostic data were obtained,and then the relevant syndrome types of the patients were judged according to the data.According to the color Doppler ultrasonographic features of thyroid nodules,the patients who met the indication of fine needle aspiration biopsy of thyroid nodules were selected and underwent fine needle aspiration biopsy of thyroid nodules before operation.To analyze the clinical diagnostic value of that the ultrasonic mode used in this study and thyroid cytopathology Bethesda report system combine dialectical classification of traditional Chinese medicine in Hashimoto's thyroiditis complicated with suspected thyroid nodules.Result:A total of 89 patients with Hashimoto's thyroiditis complicated with thyroid nodules were collected.according to the ultrasonic mode,the difference between different modes was statistically significant(P<0.05).The mode of color ultrasound is also related to the dialectical classification of traditional Chinese medicine.The patients with high malignant risk score are mainly qi depression and phlegm stagnation,phlegm and blood stasis,while those with low score are exuberant liver fire and heart liver yin deficiency.According to the study of different The Bethesda System for Reporting Thyroid Cytopathology(TBSRTC)classification,the dialectical classification of patients with higher TBSRTC classification was more inclined to qi depression and phlegm stagnation,phlegm and blood stasis,and there was significant difference between different classification(P<0.05).Conclusion:Qi depression and phlegm obstruction,phlegm and blood stasis have high ultrasound malignant risk score and high TBSRTC classification grade in patients with Hashimoto's thyroiditis complicated with suspected thyroid nodules,which has important clinical diagnostic value.展开更多
Multi-label text categorization refers to the problem of categorizing text througha multi-label learning algorithm. Text classification for Asian languages such as Chinese isdifferent from work for other languages suc...Multi-label text categorization refers to the problem of categorizing text througha multi-label learning algorithm. Text classification for Asian languages such as Chinese isdifferent from work for other languages such as English which use spaces to separate words.Before classifying text, it is necessary to perform a word segmentation operation to converta continuous language into a list of separate words and then convert it into a vector of acertain dimension. Generally, multi-label learning algorithms can be divided into twocategories, problem transformation methods and adapted algorithms. This work will usecustomer's comments about some hotels as a training data set, which contains labels for allaspects of the hotel evaluation, aiming to analyze and compare the performance of variousmulti-label learning algorithms on Chinese text classification. The experiment involves threebasic methods of problem transformation methods: Support Vector Machine, Random Forest,k-Nearest-Neighbor;and one adapted algorithm of Convolutional Neural Network. Theexperimental results show that the Support Vector Machine has better performance.展开更多
The expanding role of the Chinese language in international communications has become increasingly prominent as China’s comprehensive national power continues to grow,leading to a significant rise in the number of Ch...The expanding role of the Chinese language in international communications has become increasingly prominent as China’s comprehensive national power continues to grow,leading to a significant rise in the number of Chinese language learners.Since online teaching is not limited by time and space,its application is widespread.For beginners in the Chinese language,the Chinese characters are both a priority and a challenge.The“Chinese Character Classification,”also known as the“Six Writings,”is the earliest systematic theory of Chinese character structures,and teaching Chinese characters in categories based on the“Chinese Character Classification”is a method that fits the cognition of beginners.In order to teach Chinese characters in a targeted approach,based on the collection and analysis of the common errors of Chinese characters among beginners,(1)this paper proposes that(a)the intuitive method can be applied to teach pictographic characters,indicative characters,and associative compound characters in online teaching;(b)the inductive-deductive method of“basic characters to new characters”can be applied for the teaching of pictophonetic characters and associative compound characters;(c)the learning of character patterns should be approached in a whole-part-whole process,while importance should be attached to the suggestion of the frequency effect with a view to facilitating the online learning of Chinese characters for beginners.The aim of this paper is to provide some practical implications for the online teaching of Chinese characters to foreigners.展开更多
Differences between healthy subjects and associated disease risks are of substantial interest in clinical medicine. Based on clinical presentations, Traditional Chinese Medicine (TCM) classifies healthy people into ...Differences between healthy subjects and associated disease risks are of substantial interest in clinical medicine. Based on clinical presentations, Traditional Chinese Medicine (TCM) classifies healthy people into nine constitutions: Balanced, Qi, Yang or Yin deficiency, Phlegm-dampness, Damp-heat, Blood stasis, Qi stagnation, and Inherited special constitutions. In particular, Yang and Yin deficiency constitutions exhibit cold and heat aversion, respectively. However, the intrinsic molecular characteristics of unbal- anced phenotypes remain unclear. To determine whether gene expression-based clustering can reca- pitulate TCM-based classification, peripheral blood mononudear cells (PBMCs) were collected from Chinese Han individuals with Yang/Yin deficiency (n = 12 each) and Balanced (n = 8) constitutions, and global gene expression profiles were determined using the Affymetrix HC-UI33A Plus 2.0 array. Notably, we found that gene expression-based classifications reflected distinct TCM-based subtypes. Consistent with the clinical observation that subjects with Yang deficiency tend toward obesity, series-clustering analysis detected several key lipid metabolic genes (diacylglycerol acyltransferase (DGAT2), acyl-CoA synthetase (ACSL1), and ATP-hinding cassette subfamily A member 1 (ABCAI)) to be down- and up- regulated in Yin and Yang deficiency constitutions, respectively. Our findings suggest that Yin]Yang deficiency and Balanced constitutions are unique entities in their mRNA expression profiles. Moreover, the distinct physical and clinical characteristics of each unbalanced constitution can be explained, in part, by specific gene expression signatures.展开更多
Objective: To determine whether patterns of enterovirus 71(EV71)-associated hand, foot, and mouth disease(HFMD) were classified based on symptoms and signs, and explore whether individual characteristics were cor...Objective: To determine whether patterns of enterovirus 71(EV71)-associated hand, foot, and mouth disease(HFMD) were classified based on symptoms and signs, and explore whether individual characteristics were correlated with membership in particular pattern. Methods: Symptom-based latent class analysis(LCA) was used to determine whether patterns of EV71-HFMD existed in a sample of 433 cases from a clinical data warehouse system. Logistic regression was then performed to explore whether demographic, and laboratory data were associated with pattern membership. Results: LCA demonstrated a two-subgroup solution with an optimal fit, deduced according to the Bayesian Information Criterion minima. Hot pattern(59.1% of all patients) was characterized by a very high fever and high endorsement rates for classical HFMD symptoms(i.e., rash on the extremities, blisters, and oral mucosa lesions). Non-hot pattern(40.9% of all patients) was characterized by classical HFMD symptoms. The multiple logistic regression results suggest that white blood cell counts and aspartate transaminase were positively correlated with the hot pattern(adjust odds ratio=1.07, 95% confidence interval: 1.006–1.115; adjust odds ratio=1.051, 95% confidence interval: 1.019–1.084; respectively). Conclusions: LCA on reported symptoms and signs in a retrospective study allowed different subgroups with meaningful clinical correlates to be defined. These findings provide evidence for targeted prevention and treatment interventions.展开更多
Objective:To develop a multimodal deep-learning model for classifying Chinese medicine constitution,i.e.,the balanced and unbalanced constitutions,based on inspection of tongue and face images,pulse waves from palpati...Objective:To develop a multimodal deep-learning model for classifying Chinese medicine constitution,i.e.,the balanced and unbalanced constitutions,based on inspection of tongue and face images,pulse waves from palpation,and health information from a total of 540 subjects.Methods:This study data consisted of tongue and face images,pulse waves obtained by palpation,and health information,including personal information,life habits,medical history,and current symptoms,from 540 subjects(202 males and 338 females).Convolutional neural networks,recurrent neural networks,and fully connected neural networks were used to extract deep features from the data.Feature fusion and decision fusion models were constructed for the multimodal data.Results:The optimal models for tongue and face images,pulse waves and health information were ResNet18,Gate Recurrent Unit,and entity embedding,respectively.Feature fusion was superior to decision fusion.The multimodal analysis revealed that multimodal data compensated for the loss of information from a single mode,resulting in improved classification performance.Conclusions:Multimodal data fusion can supplement single model information and improve classification performance.Our research underscores the effectiveness of multimodal deep learning technology to identify body constitution for modernizing and improving the intelligent application of Chinese medicine.展开更多
Purpose: This study aims to discuss the strategies for mapping from Dewey Decimal Classification(DDC) numbers to Chinese Library Classification(CLC) numbers based on co-occurrence mapping while minimizing manual inter...Purpose: This study aims to discuss the strategies for mapping from Dewey Decimal Classification(DDC) numbers to Chinese Library Classification(CLC) numbers based on co-occurrence mapping while minimizing manual intervention.Design/methodology/approach: Several statistical tables were created based on frequency counts of the mapping relations with samples of USMARC records,which contain both DDC and CLC numbers. A manual table was created through direct mapping. In order to find reasonable mapping strategies,the mapping results were compared from three aspects including the sample size,the choice between one-to-one and one-to-multiple mapping relations,and the role of a manual mapping table.Findings: Larger sample size provides more DDC numbers in the mapping table. The statistical table including one-to-multiple DDC-CLC relations provides a higher ratio of correct matches than that including only one-to-one relations. The manual mapping table cannot produce a better result than the statistical tables. Therefore,we should make full use of statistical mapping tables and avoid the time-consuming manual mapping as much as possible.Research limitations: All the sample sizes were small. We did not consider DDC editions in our study. One-to-multiple DDC-CLC relations in the records were collected in the mapping table,but how to select one appropriate CLC number in the matching process needs to be further studied.Practical implications: The ratio of correct matches based on the statistical mapping table came up to about 90% by CLC top-level classes and 76% by the second-level classes in our study. The statistical mapping table will be improved to realize the automatic classification of e-resources and shorten the cataloging cycle significantly.Originality/value: The mapping results were investigated from different aspects in order to find suitable mapping strategies from DDC to CLC while minimizing manual intervention.The findings have facilitated the establishment of DDC-CLC mapping system for practical applications.展开更多
With the rapid growth of information retrieval technology,Chinese text classification,which is the basis of information content security,has become a widely discussed topic.In view of the huge difference compared with...With the rapid growth of information retrieval technology,Chinese text classification,which is the basis of information content security,has become a widely discussed topic.In view of the huge difference compared with English,Chinese text task is more complex in semantic information representations.However,most existing Chinese text classification approaches typically regard feature representation and feature selection as the key points,but fail to take into account the learning strategy that adapts to the task.Besides,these approaches compress the Chinese word into a representation vector,without considering the distribution of the term among the categories of interest.In order to improve the effect of Chinese text classification,a unified method,called Supervised Contrastive Learning with Term Weighting(SCL-TW),is proposed in this paper.Supervised contrastive learning makes full use of a large amount of unlabeled data to improve model stability.In SCL-TW,we calculate the score of term weighting to optimize the process of data augmentation of Chinese text.Subsequently,the transformed features are fed into a temporal convolution network to conduct feature representation.Experimental verifications are conducted on two Chinese benchmark datasets.The results demonstrate that SCL-TW outperforms other advanced Chinese text classification approaches by an amazing margin.展开更多
Biological complexity and the need for personalized medicine means that biomarker development has become increasingly challenging.Thus,new paradigms for research need to be created that bring together a different clas...Biological complexity and the need for personalized medicine means that biomarker development has become increasingly challenging.Thus,new paradigms for research need to be created that bring together a different classifier of individuals.One potential solution is collaboration between biomarker development and Chinese medicine pattern classification.In this article,two examples of rheumatoid arthritis are discussed,including a new biomarker candidate casein kinase 2 interacting protein 1(CKIP-1)and a micro RNA 214.The authors obtained a"snapshot"of pattern classification with disease in biomarker identification.Bioinformatics analyses revealed underlying biological functions of two biomarker candidates,in varying degrees,are correlated with Chinese medicine pattern of rheumatoid arthritis.The authors'initial attempt can provide a new window for studying the win-win potential correlation between the biomarkers and pattern classification in Chinese medicine.展开更多
Rice bran oil is a healthy oil from many aspects.The oil has a balanced fatty acid profile comparing with many other vegetable oils.The key difference is the minor components or micronutrients or unsaponifiable matter...Rice bran oil is a healthy oil from many aspects.The oil has a balanced fatty acid profile comparing with many other vegetable oils.The key difference is the minor components or micronutrients or unsaponifiable matters contained in the oil that are very special and in larger percentages.The oil contains more than 1.5%oryzanol that gives nutritional and pharmaceutical functions from the studies so far.More studies are needed to demonstrate the wide functions in many aspects.The oil also contains large percentage of phytosterols which received huge amount of studies for nutritional applications.Furthermore,the oil contains tocopherols and tocotrienols,in which for the later particularly it gives many special functions including prevention of breast cancers for example.When the oil is properly processed and used in foods,those functions are more and more demonstrated in nutritional or biological studies.Thus the oil in food and pharmaceutical applications is in exploring both in academic studies and industrial practice.In this work,an overview of such progress is given.展开更多
This article focuses the category status of Chinese herbal medicine in the United States where it has been mistakenly classified as a dietary supplement. According to Yellow Emperor Canon of Internal Medicine(Huang D...This article focuses the category status of Chinese herbal medicine in the United States where it has been mistakenly classified as a dietary supplement. According to Yellow Emperor Canon of Internal Medicine(Huang Di Nei Jing), clinical treatment in broad sense is to apply certain poisonous medicines to fight against pathogeneses, by which all medicines have certain toxicity and side effect. From ancient times to modern society, all, or at least most, practitioners have used herbal medicine to treat patients' medical conditions. The educational curriculums in Chinese medicine(CM) comprise the courses of herbal medicine(herbology) and herbal formulae. The objective of these courses is to teach students to use herbal medicine or formulae to treat disease as materia medica. In contrast, dietary supplements are preparations intended to provide nutrients that are missing or are not consumed in sufficient quantity in a person's diet. In contrast, Chinese herbs can be toxic, which have been proven through laboratory research. Both clinical practice and research have demonstrated that Chinese herbal medicine is a special type of natural materia medica, not a dietary supplement.展开更多
Population aging is a worldwide problem, with the development of economy, the aging of the population problem of old-age security puts forward a new challenge. This paper on China's current pension service policy on ...Population aging is a worldwide problem, with the development of economy, the aging of the population problem of old-age security puts forward a new challenge. This paper on China's current pension service policy on the content classification, and summarizes its transformation, finally puts forward several opinions to pension policy reform.展开更多
The development of an effective classification method for human health conditions is essential for precise diagnosis and delivery of tailored therapy to individuals. Contemporary classification of disease systems has ...The development of an effective classification method for human health conditions is essential for precise diagnosis and delivery of tailored therapy to individuals. Contemporary classification of disease systems has properties that limit its information content and usability. Chinese medicine pattern classification has been incorporated with disease classification, and this integrated classification method became more precise because of the increased understanding of the molecular mechanisms. However, we are still facing the complexity of diseases and patterns in the classification of health conditions. With continuing advances in omics methodologies and instrumentation, we are proposing a new classification approach: molecular module classification, which is applying molecular modules to classifying human health status. The initiative would be precisely defining the health status, providing accurate diagnoses, optimizing the therapeutics and improving new drug discovery strategy. Therefore, there would be no current disease diagnosis, no disease pattern classification, and in the future, a new medicine based on this classification, molecular module medicine, could redefine health statuses and reshape the clinical practice.展开更多
文摘The Chinese Neurology and Psychiatry Association conducted a national field trial of its Chinese Classification and Diagnostic Criteria of Mental Disorders (CCMD-2) involov-ing 26 provinces and municipalities, 80 psychiatric institutes, and 224 professionals. The results were as follows: (1)95.2% of researchers considered the comprehensibility of the CCMD-2 diagnstic criteria good. Within the ten major categories, comprehensibility ranged from 85.7% to 100%. (2) Of those surveyed concerning the acceptibility of the CCCMD-2 diagnostic criteria, 85.9% considered them acceptable. In individual classifications, the rate ranged from 74.1% to 95.2%. (3) 1498 cases were tested. The overall applicability rate which indicated the consistency between the CCMD-2 result and the actual clinical diagnoses was found to be 87.6%, (averaging Kappa = 0.82,P<0.01), better than those obtained from non-Chinese systems of diagnosis.
基金Project(KC18071)supported by the Application Foundation Research Program of Xuzhou,ChinaProjects(2017YFC0804401,2017YFC0804409)supported by the National Key R&D Program of China
文摘The sharp increase of the amount of Internet Chinese text data has significantly prolonged the processing time of classification on these data.In order to solve this problem,this paper proposes and implements a parallel naive Bayes algorithm(PNBA)for Chinese text classification based on Spark,a parallel memory computing platform for big data.This algorithm has implemented parallel operation throughout the entire training and prediction process of naive Bayes classifier mainly by adopting the programming model of resilient distributed datasets(RDD).For comparison,a PNBA based on Hadoop is also implemented.The test results show that in the same computing environment and for the same text sets,the Spark PNBA is obviously superior to the Hadoop PNBA in terms of key indicators such as speedup ratio and scalability.Therefore,Spark-based parallel algorithms can better meet the requirement of large-scale Chinese text data mining.
基金Supported by the China Postdoctoral Science Foundation
文摘We explore the techniques of utilizing N gram information to categorize Chinese text documents hierarchically so that the classifier can shake off the burden of large dictionaries and complex segmentation processing, and subsequently be domain and time independent. A hierarchical Chinese text classifier is implemented. Experimental results show that hierarchically classifying Chinese text documents based N grams can achieve satisfactory performance and outperforms the other traditional Chinese text classifiers.
基金This work was supported by Ministry of public security technology research program[Grant No.2020JSYJC22ok]Fundamental Research Funds for the Central Universities(No.2021JKF215)+1 种基金Open Research Fund of the Public Security Behavioral Science Laboratory,People’s Public Security University of China(2020SYS03)Police and people build/share a smart community(PJ13-201912-0525).
文摘With the explosive growth of Internet text information,the task of text classification is more important.As a part of text classification,Chinese news text classification also plays an important role.In public security work,public opinion news classification is an important topic.Effective and accurate classification of public opinion news is a necessary prerequisite for relevant departments to grasp the situation of public opinion and control the trend of public opinion in time.This paper introduces a combinedconvolutional neural network text classification model based on word2vec and improved TF-IDF:firstly,the word vector is trained through word2vec model,then the weight of each word is calculated by using the improved TFIDF algorithm based on class frequency variance,and the word vector and weight are combined to construct the text vector representation.Finally,the combined-convolutional neural network is used to train and test the Thucnews data set.The results show that the classification effect of this model is better than the traditional Text-RNN model,the traditional Text-CNN model and word2vec-CNN model.The test accuracy is 97.56%,the accuracy rate is 97%,the recall rate is 97%,and the F1-score is 97%.
文摘Objective:To explore the diagnostic value of traditional Chinese medical(TCM)dialectical classification in Hashimoto's thyroiditis complicated with suspicious nodules.Methods:The clinical data of patients with Hashimoto's thyroiditis complicated with thyroid nodules in the Department of Breast and thyroid surgery of Weifang Hospital of traditional Chinese Medicine from January 2018 to December 2019 were collected.The patients were examined by 2 or more experienced TCM doctors,and the four diagnostic data were obtained,and then the relevant syndrome types of the patients were judged according to the data.According to the color Doppler ultrasonographic features of thyroid nodules,the patients who met the indication of fine needle aspiration biopsy of thyroid nodules were selected and underwent fine needle aspiration biopsy of thyroid nodules before operation.To analyze the clinical diagnostic value of that the ultrasonic mode used in this study and thyroid cytopathology Bethesda report system combine dialectical classification of traditional Chinese medicine in Hashimoto's thyroiditis complicated with suspected thyroid nodules.Result:A total of 89 patients with Hashimoto's thyroiditis complicated with thyroid nodules were collected.according to the ultrasonic mode,the difference between different modes was statistically significant(P<0.05).The mode of color ultrasound is also related to the dialectical classification of traditional Chinese medicine.The patients with high malignant risk score are mainly qi depression and phlegm stagnation,phlegm and blood stasis,while those with low score are exuberant liver fire and heart liver yin deficiency.According to the study of different The Bethesda System for Reporting Thyroid Cytopathology(TBSRTC)classification,the dialectical classification of patients with higher TBSRTC classification was more inclined to qi depression and phlegm stagnation,phlegm and blood stasis,and there was significant difference between different classification(P<0.05).Conclusion:Qi depression and phlegm obstruction,phlegm and blood stasis have high ultrasound malignant risk score and high TBSRTC classification grade in patients with Hashimoto's thyroiditis complicated with suspected thyroid nodules,which has important clinical diagnostic value.
基金supported by the NSFC (Grant Nos. 61772281,61703212, 61602254)Jiangsu Province Natural Science Foundation [grant numberBK2160968]the Priority Academic Program Development of Jiangsu Higher Edu-cationInstitutions (PAPD) and Jiangsu Collaborative Innovation Center on AtmosphericEnvironment and Equipment Technology (CICAEET).
文摘Multi-label text categorization refers to the problem of categorizing text througha multi-label learning algorithm. Text classification for Asian languages such as Chinese isdifferent from work for other languages such as English which use spaces to separate words.Before classifying text, it is necessary to perform a word segmentation operation to converta continuous language into a list of separate words and then convert it into a vector of acertain dimension. Generally, multi-label learning algorithms can be divided into twocategories, problem transformation methods and adapted algorithms. This work will usecustomer's comments about some hotels as a training data set, which contains labels for allaspects of the hotel evaluation, aiming to analyze and compare the performance of variousmulti-label learning algorithms on Chinese text classification. The experiment involves threebasic methods of problem transformation methods: Support Vector Machine, Random Forest,k-Nearest-Neighbor;and one adapted algorithm of Convolutional Neural Network. Theexperimental results show that the Support Vector Machine has better performance.
基金an outcome of the project of Sichuan University,“A Preliminary Study on Online Chinese Character Teaching Strategies for Teaching Chinese as a Foreign Language During the COVID-19 Pandemic,”Project No.2022 Self-Research-Overseas 008。
文摘The expanding role of the Chinese language in international communications has become increasingly prominent as China’s comprehensive national power continues to grow,leading to a significant rise in the number of Chinese language learners.Since online teaching is not limited by time and space,its application is widespread.For beginners in the Chinese language,the Chinese characters are both a priority and a challenge.The“Chinese Character Classification,”also known as the“Six Writings,”is the earliest systematic theory of Chinese character structures,and teaching Chinese characters in categories based on the“Chinese Character Classification”is a method that fits the cognition of beginners.In order to teach Chinese characters in a targeted approach,based on the collection and analysis of the common errors of Chinese characters among beginners,(1)this paper proposes that(a)the intuitive method can be applied to teach pictographic characters,indicative characters,and associative compound characters in online teaching;(b)the inductive-deductive method of“basic characters to new characters”can be applied for the teaching of pictophonetic characters and associative compound characters;(c)the learning of character patterns should be approached in a whole-part-whole process,while importance should be attached to the suggestion of the frequency effect with a view to facilitating the online learning of Chinese characters for beginners.The aim of this paper is to provide some practical implications for the online teaching of Chinese characters to foreigners.
基金supported by the National Key Basic Research Program of China (973 Program No. 2011CB505400)
文摘Differences between healthy subjects and associated disease risks are of substantial interest in clinical medicine. Based on clinical presentations, Traditional Chinese Medicine (TCM) classifies healthy people into nine constitutions: Balanced, Qi, Yang or Yin deficiency, Phlegm-dampness, Damp-heat, Blood stasis, Qi stagnation, and Inherited special constitutions. In particular, Yang and Yin deficiency constitutions exhibit cold and heat aversion, respectively. However, the intrinsic molecular characteristics of unbal- anced phenotypes remain unclear. To determine whether gene expression-based clustering can reca- pitulate TCM-based classification, peripheral blood mononudear cells (PBMCs) were collected from Chinese Han individuals with Yang/Yin deficiency (n = 12 each) and Balanced (n = 8) constitutions, and global gene expression profiles were determined using the Affymetrix HC-UI33A Plus 2.0 array. Notably, we found that gene expression-based classifications reflected distinct TCM-based subtypes. Consistent with the clinical observation that subjects with Yang deficiency tend toward obesity, series-clustering analysis detected several key lipid metabolic genes (diacylglycerol acyltransferase (DGAT2), acyl-CoA synthetase (ACSL1), and ATP-hinding cassette subfamily A member 1 (ABCAI)) to be down- and up- regulated in Yin and Yang deficiency constitutions, respectively. Our findings suggest that Yin]Yang deficiency and Balanced constitutions are unique entities in their mRNA expression profiles. Moreover, the distinct physical and clinical characteristics of each unbalanced constitution can be explained, in part, by specific gene expression signatures.
基金Supported by the Nation Health and Family Planning Commission of China(No.2012ZX10005009)Fundamental Research Funds for the Central Public Welfare Research Institutes(No.Z0474)National Natural Science Foundation of China(No.81503679)
文摘Objective: To determine whether patterns of enterovirus 71(EV71)-associated hand, foot, and mouth disease(HFMD) were classified based on symptoms and signs, and explore whether individual characteristics were correlated with membership in particular pattern. Methods: Symptom-based latent class analysis(LCA) was used to determine whether patterns of EV71-HFMD existed in a sample of 433 cases from a clinical data warehouse system. Logistic regression was then performed to explore whether demographic, and laboratory data were associated with pattern membership. Results: LCA demonstrated a two-subgroup solution with an optimal fit, deduced according to the Bayesian Information Criterion minima. Hot pattern(59.1% of all patients) was characterized by a very high fever and high endorsement rates for classical HFMD symptoms(i.e., rash on the extremities, blisters, and oral mucosa lesions). Non-hot pattern(40.9% of all patients) was characterized by classical HFMD symptoms. The multiple logistic regression results suggest that white blood cell counts and aspartate transaminase were positively correlated with the hot pattern(adjust odds ratio=1.07, 95% confidence interval: 1.006–1.115; adjust odds ratio=1.051, 95% confidence interval: 1.019–1.084; respectively). Conclusions: LCA on reported symptoms and signs in a retrospective study allowed different subgroups with meaningful clinical correlates to be defined. These findings provide evidence for targeted prevention and treatment interventions.
基金Supported by the National Key Research and Development Program of China Under Grant(No.2018YFC1707704)。
文摘Objective:To develop a multimodal deep-learning model for classifying Chinese medicine constitution,i.e.,the balanced and unbalanced constitutions,based on inspection of tongue and face images,pulse waves from palpation,and health information from a total of 540 subjects.Methods:This study data consisted of tongue and face images,pulse waves obtained by palpation,and health information,including personal information,life habits,medical history,and current symptoms,from 540 subjects(202 males and 338 females).Convolutional neural networks,recurrent neural networks,and fully connected neural networks were used to extract deep features from the data.Feature fusion and decision fusion models were constructed for the multimodal data.Results:The optimal models for tongue and face images,pulse waves and health information were ResNet18,Gate Recurrent Unit,and entity embedding,respectively.Feature fusion was superior to decision fusion.The multimodal analysis revealed that multimodal data compensated for the loss of information from a single mode,resulting in improved classification performance.Conclusions:Multimodal data fusion can supplement single model information and improve classification performance.Our research underscores the effectiveness of multimodal deep learning technology to identify body constitution for modernizing and improving the intelligent application of Chinese medicine.
基金jointly supported by the Foundation for Humanities and Social Sciences of the Chinese Ministryof Education(Grant No.:11BTQ007)Shanghai Society for Library Science(Grant No.:10BSTX02)
文摘Purpose: This study aims to discuss the strategies for mapping from Dewey Decimal Classification(DDC) numbers to Chinese Library Classification(CLC) numbers based on co-occurrence mapping while minimizing manual intervention.Design/methodology/approach: Several statistical tables were created based on frequency counts of the mapping relations with samples of USMARC records,which contain both DDC and CLC numbers. A manual table was created through direct mapping. In order to find reasonable mapping strategies,the mapping results were compared from three aspects including the sample size,the choice between one-to-one and one-to-multiple mapping relations,and the role of a manual mapping table.Findings: Larger sample size provides more DDC numbers in the mapping table. The statistical table including one-to-multiple DDC-CLC relations provides a higher ratio of correct matches than that including only one-to-one relations. The manual mapping table cannot produce a better result than the statistical tables. Therefore,we should make full use of statistical mapping tables and avoid the time-consuming manual mapping as much as possible.Research limitations: All the sample sizes were small. We did not consider DDC editions in our study. One-to-multiple DDC-CLC relations in the records were collected in the mapping table,but how to select one appropriate CLC number in the matching process needs to be further studied.Practical implications: The ratio of correct matches based on the statistical mapping table came up to about 90% by CLC top-level classes and 76% by the second-level classes in our study. The statistical mapping table will be improved to realize the automatic classification of e-resources and shorten the cataloging cycle significantly.Originality/value: The mapping results were investigated from different aspects in order to find suitable mapping strategies from DDC to CLC while minimizing manual intervention.The findings have facilitated the establishment of DDC-CLC mapping system for practical applications.
基金supported by the National Natural Science Foundation of China (No.U1936122)Primary Research&Developement Plan of Hubei Province (Nos.2020BAB101 and 2020BAA003).
文摘With the rapid growth of information retrieval technology,Chinese text classification,which is the basis of information content security,has become a widely discussed topic.In view of the huge difference compared with English,Chinese text task is more complex in semantic information representations.However,most existing Chinese text classification approaches typically regard feature representation and feature selection as the key points,but fail to take into account the learning strategy that adapts to the task.Besides,these approaches compress the Chinese word into a representation vector,without considering the distribution of the term among the categories of interest.In order to improve the effect of Chinese text classification,a unified method,called Supervised Contrastive Learning with Term Weighting(SCL-TW),is proposed in this paper.Supervised contrastive learning makes full use of a large amount of unlabeled data to improve model stability.In SCL-TW,we calculate the score of term weighting to optimize the process of data augmentation of Chinese text.Subsequently,the transformed features are fed into a temporal convolution network to conduct feature representation.Experimental verifications are conducted on two Chinese benchmark datasets.The results demonstrate that SCL-TW outperforms other advanced Chinese text classification approaches by an amazing margin.
基金Supported by the National Natural Science Foundation of China(No.81503449,81673773)。
文摘Biological complexity and the need for personalized medicine means that biomarker development has become increasingly challenging.Thus,new paradigms for research need to be created that bring together a different classifier of individuals.One potential solution is collaboration between biomarker development and Chinese medicine pattern classification.In this article,two examples of rheumatoid arthritis are discussed,including a new biomarker candidate casein kinase 2 interacting protein 1(CKIP-1)and a micro RNA 214.The authors obtained a"snapshot"of pattern classification with disease in biomarker identification.Bioinformatics analyses revealed underlying biological functions of two biomarker candidates,in varying degrees,are correlated with Chinese medicine pattern of rheumatoid arthritis.The authors'initial attempt can provide a new window for studying the win-win potential correlation between the biomarkers and pattern classification in Chinese medicine.
文摘Rice bran oil is a healthy oil from many aspects.The oil has a balanced fatty acid profile comparing with many other vegetable oils.The key difference is the minor components or micronutrients or unsaponifiable matters contained in the oil that are very special and in larger percentages.The oil contains more than 1.5%oryzanol that gives nutritional and pharmaceutical functions from the studies so far.More studies are needed to demonstrate the wide functions in many aspects.The oil also contains large percentage of phytosterols which received huge amount of studies for nutritional applications.Furthermore,the oil contains tocopherols and tocotrienols,in which for the later particularly it gives many special functions including prevention of breast cancers for example.When the oil is properly processed and used in foods,those functions are more and more demonstrated in nutritional or biological studies.Thus the oil in food and pharmaceutical applications is in exploring both in academic studies and industrial practice.In this work,an overview of such progress is given.
文摘This article focuses the category status of Chinese herbal medicine in the United States where it has been mistakenly classified as a dietary supplement. According to Yellow Emperor Canon of Internal Medicine(Huang Di Nei Jing), clinical treatment in broad sense is to apply certain poisonous medicines to fight against pathogeneses, by which all medicines have certain toxicity and side effect. From ancient times to modern society, all, or at least most, practitioners have used herbal medicine to treat patients' medical conditions. The educational curriculums in Chinese medicine(CM) comprise the courses of herbal medicine(herbology) and herbal formulae. The objective of these courses is to teach students to use herbal medicine or formulae to treat disease as materia medica. In contrast, dietary supplements are preparations intended to provide nutrients that are missing or are not consumed in sufficient quantity in a person's diet. In contrast, Chinese herbs can be toxic, which have been proven through laboratory research. Both clinical practice and research have demonstrated that Chinese herbal medicine is a special type of natural materia medica, not a dietary supplement.
文摘Population aging is a worldwide problem, with the development of economy, the aging of the population problem of old-age security puts forward a new challenge. This paper on China's current pension service policy on the content classification, and summarizes its transformation, finally puts forward several opinions to pension policy reform.
文摘The development of an effective classification method for human health conditions is essential for precise diagnosis and delivery of tailored therapy to individuals. Contemporary classification of disease systems has properties that limit its information content and usability. Chinese medicine pattern classification has been incorporated with disease classification, and this integrated classification method became more precise because of the increased understanding of the molecular mechanisms. However, we are still facing the complexity of diseases and patterns in the classification of health conditions. With continuing advances in omics methodologies and instrumentation, we are proposing a new classification approach: molecular module classification, which is applying molecular modules to classifying human health status. The initiative would be precisely defining the health status, providing accurate diagnoses, optimizing the therapeutics and improving new drug discovery strategy. Therefore, there would be no current disease diagnosis, no disease pattern classification, and in the future, a new medicine based on this classification, molecular module medicine, could redefine health statuses and reshape the clinical practice.