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Symptom selection for multi-label data of inquiry diagnosis in traditional Chinese medicine

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Science China(Information Sciences) 2013年第5期56卷 238-250页

作者： SHAO Huan LI GuoZheng LIU GuoPing wang yiqin School of Computer Engineering and Science Shanghai University Department of Control Science and Engineering Key Laboratory of Ministry of Education for Service Computing and Embedded SystemsTongji University Laboratory of Information Access and Synthesis of TCM Four Diagnosis Shanghai University of Traditional Chinese Medicine

In traditional Chinese medicine(TCM) diagnosis,a patient may be associated with more than one syndrome tags,and its computer-aided diagnosis is a typical application in the domain of multi-label learning of high-dimensional *** is common that a great deal of symptoms can occur in traditional Chinese medical diagnosis,which affects the modeling of diagnostic *** selection entails choosing the smallest feature subset of relevant symptoms,and maximizing the generalization performance of the *** present there are rare researches on feature selection on multi-label data.A hybrid optimization technique is introduced to symptom selection for multi-label data in TCM diagnosis in this paper,and modeling is made by means of four multi-label learning algorithms like k nearest neighbors,*** compare the performance of the algorithm with the current popular dimension reduction algorithms like MEFS(embedded feature selection for multi-Label learning),MDDM(multi-label dimensionality reduction via dependence maximization) on the UCI Yeast gene functional data set and an inquiry diagnosis dataset of coronary heart disease(CHD).Experimental results show that the algorithm we present has significantly improved the *** particular,the improvement on the average precision for the classifier is up to 10.62% and 14.54%.Syndrome inquiry modeling of CHD in TCM is realized in this paper,providing effective reference for the diagnosis of CHD and analysis of other multi-label data.

关键词： multi-label learning feature selection high-dimensionality inquiry of traditional Chinese medicine coronary heart disease

Recurrence quantification analysis on pulse morphological changes in patients with coronary heart disease

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Journal of Traditional Chinese Medicine 2012年第4期32卷 571-577页

作者： Rui Guo yiqin wang Jianjun Yan Hanxia Yan Laboratory of Synthetic Study on TCM Diagnostic Information Shanghai University of Traditional Chinese Medicine Center for Mechatronics Engineering East China University of Science and Technology

OBJECTIVE： To show that the pulse diagnosis used in Traditional Chinese Medicine, combined with nonlinear dynamic analysis, can help identify car- diovascular diseases. METHODS： Recurrence quantification analysis （RQA） was used to study pulse morphological changes in 37 inpatients with coronary heart dis- ease （CHD） and 37 normal subjects （controls）. An in- dependent sample t-test detected significant differ- ences in RQA measures of their pulses. A support vector machine （SVM） classified the groups accord- ing to their RQA measures. Classic time-domain pa- rameters were used for comparison. RESULTS： RQA measures can be divided into two groups. One group of measures [ecurrence rate（RR）, determinism （DEL）, average diagonal line length （L）, maximum length of diagonal structures （Lmax）, Shannon entropy of the frequency distribu- tion of diagonal line lengths （ENTR）, laminarity （LAM）, average length of vertical structures （TT）, maximum length of vertical structures （Vmax）] showed significantly higher values for patients with CHD than for normal subjects （P〈0.0S）. The other measures （RR_std, L_std, Lmaxstd, TT_std, Vmax_std） showed significantly lower values for the CHD group than for normal subjects （P〈0.05）. SVM classification accuracy was higher with RQA measures： With RQA （16 parameters） accuracy was at 88.21%, and with RQA（12 parameters） accuracy was at 84.11%. In contrast, with classic time-do- main （15 parameters） accuracy was 75.73%, and with time-domain （7 parameters） accuracy was 74.7O%. CONCLUSION： Nonlinear dynamic methods such as RQA can be used to study functional and struc- tural changes in the pulse noninvasively. Pulse sig- nals of individuals with CHD have greater regulari- ty, determinism, and stability than normal subjects, and their pulse morphology displays less variabili- ty. RQA can distinguish the CHD pulse from the healthy pulse with an accuracy of 88.21%, thereby providing an early diagnosis of cardiovascular dis- eases such as CHD.

关键词： Pulse-taking Cardiovascular diseases Recurrence quantification analysis

Multi-VMs Intrusion Detection for Cloud Security Using Dempster-shafer Theory

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Computers, Materials & Continua 2018年第11期57卷 297-306页

作者： Chak Fong Cheang yiqin wang Zhiping Cai Gen Xu Faculty of Information Technology Macao University of Science and TechnologyMacao College of Computer National University of Defense TechnologyChangsha410073China

Cloud computing provides easy and on-demand access to computing resources in a configurable *** flexibility of the cloud environment attracts more and more network services to be deployed on the cloud using groups of virtual machines(VMs),instead of being restricted on a single physical *** more and more network services are deployed on the cloud,the detection of the intrusion likes Distributed Denialof-Service(DDoS)attack becomes much more challenging than that on the traditional servers because even a single network service now is possibly provided by groups of VMs across the cloud *** this paper,we propose a cloud-based intrusion detection system(IDS)which inspects the features of data flow between neighboring VMs,analyzes the probability of being attacked on each pair of VMs and then regards it as independent evidence using Dempster-Shafer theory,and eventually combines the evidence among all pairs of VMs using the method of evidence *** the traditional IDS that focus on analyzing the entire network service externally,our proposed algorithm makes full use of the internal interactions between VMs,and the experiment proved that it can provide more accurate results than the traditional algorithm.

关键词： Intrusion detection cloud computing Dempster-Shafer theory evidence fusion

Nitric oxide: promoter or suppressor of programmed cell death?

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Protein & Cell 2010年第2期1卷 133-142页

作者： yiqin wang Chen Chen Gary J.Loake Chengcai Chu National Key Laboratory of Plant Genomics and National Centre for Plant Gene Research Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijing 100101China Beijing Forestry University Beijing 100083China Institute of Molecular Plant Sciences School of Biological SciencesUniversity of EdinburghKing’s BuildingsEdinburgh EH93JRUnited Kingdom

Nitric oxide(NO)is a short-lived gaseous free radical that predominantly functions as a messenger and effector *** affects a variety of physiological processes,including programmed cell death(PCD)through cyclic guanosine monophosphate(cGMP)-dependent and-independent *** this field,dominant discoveries are the diverse apoptosis networks in mammalian cells,which involve signals primarily via death receptors(extrinsic pathway)or the mitochondria(intrinsic pathway)that recruit caspases as effector *** plants,PCD shares some similarities with animal cells,but NO is involved in PCD induction via interacting with pathways of *** has both promoting and suppressing effects on cell death,depending on a variety of factors,such as cell type,cellular redox status,and the flux and dose of local *** this article,we focus on how NO regulates the apoptotic signal cascade through protein S-nitrosylation and review the recent progress on mechanisms of PCD in both mammalian and plant cells.

关键词： nitric oxide S-nitrosylation programmed cell death

H_2O_2-induced Leaf Cell Death and the Crosstalk of Reactive Nitric/Oxygen Species

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Journal of Integrative Plant Biology 2013年第3期55卷 202-208页

作者： yiqin wang Aihong Lin Gary J. Loake Chengcai Chu State Key Laboratory of Plant Genomics and National Center for Plant Gene Research (Beijing) Institute of Genetics and Developmental Biologythe Chinese Academy of Sciences National Agricultural Technology Park Institute of Molecular Plant Sciences School of Biological SciencesUniversity of Edinburgh

In plants, the chloroplast is the main reactive oxygen species （ROS） producing site under high light stress. Catalase （CAT）, which decomposes hydrogen peroxide （H2O2）, is one of the controlling enzymes that maintains leaf redox homeostasis. The catalase mutants with reduced leaf catalase activity from different plant species exhibit an H2O2-induced leaf cell death phenotype. This phenotype was differently affected by light intensity or photoperiod, which may be caused by plant species, leaf redox status or growth conditions. In the rice CAT mutant nitric oxide excess 1 （noe1）, higher H2O2 levels induced the generation of nitric oxide （NO） and higher S-nitrosothiol （SNO） levels, suggesting that NO acts as an important endogenous mediator in H2O2-induced leaf cell death. As a free radical, NO could also react with other intracellular and extracellular targets and form a series of related molecules, collectively called reactive nitrogen species （RNS）. Recent studies have revealed that both RNS and ROS are important partners in plant leaf cell death. Here, we summarize the recent progress on H2O2-induced leaf cell death and the crosstalk of RNS and ROS signals in the plant hypersensitive response （HR）, leaf senescence, and other forms of leaf cell death triggered by diverse environmental conditions.

关键词： H2O2 induced leaf cell death hypersensitive response leaf senescence nitric oxide reactive nitrogen species reactive oxygenspecies.

Unsupervised Graph-Based Tibetan Multi-Document Summarization

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Computers, Materials & Continua 2022年第10期73卷 1769-1781页

作者： Xiaodong Yan yiqin wang Wei Song Xiaobing Zhao A.Run Yang Yanxing School of Information and Engineering Minzu University of ChinaBeijing100081China National Language Resource Monitoring&Research Center Minority Languages BranchBeijing100081China University of California IrvineCalifornia92617USA Department of Physics New Jersey Institute of TechnologyNewarkNew Jersey07102-1982USA

Text summarization creates subset that represents the most important or relevant information in the original content,which effectively reduce information *** neural network method has achieved good results in the task of text summarization both in Chinese and English,but the research of text summarization in low-resource languages is still in the exploratory stage,especially in ***’s more,there is no large-scale annotated corpus for text *** lack of dataset severely limits the development of low-resource text *** this case,unsupervised learning approaches are more appealing in low-resource languages as they do not require labeled *** this paper,we propose an unsupervised graph-based Tibetan multi-document summarization method,which divides a large number of Tibetan news documents into topics and extracts the summarization of each *** obtained by using traditional graph-based methods have high redundancy and the division of documents topics are not detailed *** terms of topic division,we adopt two level clustering methods converting original document into document-level and sentence-level graph,next we take both linguistic and deep representation into account and integrate external corpus into graph to obtain the sentence semantic *** the shortcomings of the traditional K-Means clustering method and perform more detailed clustering of *** model sentence clusters into graphs,finally remeasure sentence nodes based on the topic semantic information and the impact of topic features on sentences,higher topic relevance summary is *** order to promote the development of Tibetan text summarization,and to meet the needs of relevant researchers for high-quality Tibetan text summarization datasets,this paper manually constructs a Tibetan summarization dataset and carries out relevant *** experiment results show that our method can effectively improve the

关键词： Multi-document summarization text clustering topic feature fusion graphic model

Fractal analysis for root growth of plant seedlings under doubled CO_2 concentration

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Chinese Science Bulletin 1998年第22期43卷 1891-1893页

作者： wang yiqin ZHANG Huijuan YANG Dian’an BAI Kezhi KUANG Tingyun Shandong Teachers’University Jinan 250014China Institute of Botany Chinese Academy of SciencesBeijing 100093China.

Fractal geometry was applied and box dimension was used as an indicator to analyze the effects of doubled CO\-2 concentration on the root growth of plant seedlings. Results showed that doubled CO\-2 concentration displayed different effects on root branching characteristics of C\-3 and C\-4 plants. There was an obvious increase of root branches in spring wheat while there were no significant effects on roots of sweet sorghum. In different soil layers, root branching of spring wheat was stimulated and this promotion was most significant in the second layer (10-20 cm), which denoted that elevated CO\-2 altered the root branching pattern. That means higher CO 2 concentration influences not only root growth but also its differentiation and development.

关键词： doubled CO2 seedling root fractal dimension soil layers branching pattern.

Chinese expert consensus on fertility-preserving treatment for young women with early stage well differentiated endometrial cancer

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Gynecology and Obstetrics Clinical Medicine 2021年第1期1卷 49-53页

作者： Rong Zhou Qun Lu Guoli Liu yiqin wang Jianliu wang Peking University People's Hospital Expert Committee of Obstetrics and Gynecology of the Chinese Research Hospital AssociationChina

For young women with early stage well differentiated endometrial cancer who have fertility desire,it is import to give comprehensive assessment before initiation of conservative *** based therapy with regular assessment of treatment efficacy can achieve a promising *** complete remission patients are suggested with assisted reproductive technology or maintenance therapy depending on their immediate pregnancy *** is recommended for patients who have finished reproduction while re-treatment for recurrent cases should be carefully informed.

关键词： Fertility-preserving treatment Young women Endometrial cancer Progesterone

Characteristics of molecular classification in 52 endometrial cancer and atypical hyperplasia patients receiving fertility-sparing treatment

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Gynecology and Obstetrics Clinical Medicine 2023年第1期3卷 38-43页

作者： yiqin wang Nan Kang Liwei Li Zhiqi wang Rong Zhou Danhua Shen Jianliu wang Department of Obstetrics and Gynecology Peking University People's HospitalBeijing100044China Department of Pathology Peking University People's HospitalBeijing100044China

Objective To investigate the molecular classification of endometrial cancer(EC)and atypical endometrial hyperplasia(AEH)patients treated with fertility-sparing treatment(FST),and its relationship with clinicopathological factors and treatment ***:A total of 52EC and AEH patients who received FST and molecular classification tested by next generation sequencing in Peking University People's Hospital from June 2020 to December 2022,were retrospectively *** analyzed the relationship between molecular classification and clinicopathological factors and treatment ***(1)Of the 52 patients,including 46EC and 6 AEH patients,42(80.8%)achieved complete remission(CR)after FST,with a median time to achieve CR of 9 *** cases(23.8%)had recurrence.(2)Patients were distributed into 4 molecular subgroups as 39 cases(75%)of copy number low(CNL),7 cases(13.5%)of microsatellite instability-high(MSI-H),4 cases(7.7%)of POLE mutations(POLEmut),and 2 cases(3.8%)of copy number high(CNH).Patients with MSI-H subgroup had more family history of tumor(6/7),more with loss of expression of mismatch repair(MMR)protein(7/7),and higher expression level of Ki-67(3/3).(3)Patients with MSI-H subgroup had the lowest CR rate at 6 months(0/7,P=0.014),and survival analysis showed that such patients were less likely to achieve CR than those with CNL(P=0.022).For CNL patients,median 6-month CR rate was 40.6%.In addition,CR was obtained in 3(3/4)POLEmut patients and 2(2/2)CNH patients,*** Molecular classification relates with the treatment response in patients with EC and AEH receiving *** with MSI-H subgroup have poor treatment efficacy,and patients with CNL need to be further divided to predict treatment *** are also a few successful cases in POLEmut and CNH subtgroups,which needs further research.

关键词： Endometrial cancer Fertility-sparing Progesterone Molecular classification Efficacy