Pub Date : 2011-11-12DOI: 10.1109/BIBMW.2011.6112461
Yan Li, Biyun Xu, Shuhui Chen, Peng Liu, A. Ou, Yan Xu, Z. Wen, Biyang Ou, Ruiyu Xu, Zhaozhang Wei, Liang Zeng
To evaluate the effectiveness and safety in mild to moderate insomnia intervened by Chinese Medicine in the integrated program. Methods: Patients(18 to 56 years old) from the Five National Center, who were with mild to moderate insomnia, were randomly divided into two groups according to the central, experimental group: sleep hygiene instruction + balance acupuncture+ Chinese herbal drug; control group: sleep hygiene instruction + minor acupuncture + placebo capsules. PSQI, ISI and PSG were assessed separately after different stages of treatment and follow-up evaluation. Results: (1) Subjective and objective sleep quality: PSQI scores in the 29th days and ISI scores in the 15th days or 29th days of treatment of the experimental group were lower than the control group. PSG parameters of the experimental group were not significantly different before and after treatment. Conclusion: For patients with mild to moderate insomnia, sleep hygiene education, combined with Balance Acupuncture and Bupleurum chinense and fossil fragment and shellfish decoction can improve the subjective sleep.
{"title":"A randomized, controlled study of efficacy and safety on mild to moderate insomnia intervened by Chinese medicine in the integrated program","authors":"Yan Li, Biyun Xu, Shuhui Chen, Peng Liu, A. Ou, Yan Xu, Z. Wen, Biyang Ou, Ruiyu Xu, Zhaozhang Wei, Liang Zeng","doi":"10.1109/BIBMW.2011.6112461","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112461","url":null,"abstract":"To evaluate the effectiveness and safety in mild to moderate insomnia intervened by Chinese Medicine in the integrated program. Methods: Patients(18 to 56 years old) from the Five National Center, who were with mild to moderate insomnia, were randomly divided into two groups according to the central, experimental group: sleep hygiene instruction + balance acupuncture+ Chinese herbal drug; control group: sleep hygiene instruction + minor acupuncture + placebo capsules. PSQI, ISI and PSG were assessed separately after different stages of treatment and follow-up evaluation. Results: (1) Subjective and objective sleep quality: PSQI scores in the 29th days and ISI scores in the 15th days or 29th days of treatment of the experimental group were lower than the control group. PSG parameters of the experimental group were not significantly different before and after treatment. Conclusion: For patients with mild to moderate insomnia, sleep hygiene education, combined with Balance Acupuncture and Bupleurum chinense and fossil fragment and shellfish decoction can improve the subjective sleep.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"38 11 1","pages":"732-739"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82820955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-12DOI: 10.1109/BIBMW.2011.6112440
Sujin Kim, Desok Kim, H. Choi, H. Joo
In this study, we aimed to develop a quantitative image analysis method that may enhance the detection of the lobular carcinoma in-situ (LCIS) in breast cancer specimens. Glandular areas were segmented by using mathematical morphology from 5X histologic images of breast cancer cases (n=213). Computational features such as shape, intensity, and texture were extracted from glandular areas. Segmented glandular areas of LCIS were significantly larger, thicker, lower and less variant in intensity, compared to normal areas (Mann-Whitney test, p<0.01). Our models based on data mining algorithms detected LCIS frames at the accuracy rate close to 99%. Our proposed methods may be well incorporated into a further development of computer aided detection (CAD) software for the screening of whole slide images to locate the LCIS areas.
{"title":"Detection of lobular carcinoma in situ(LCIS) by image analysis","authors":"Sujin Kim, Desok Kim, H. Choi, H. Joo","doi":"10.1109/BIBMW.2011.6112440","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112440","url":null,"abstract":"In this study, we aimed to develop a quantitative image analysis method that may enhance the detection of the lobular carcinoma in-situ (LCIS) in breast cancer specimens. Glandular areas were segmented by using mathematical morphology from 5X histologic images of breast cancer cases (n=213). Computational features such as shape, intensity, and texture were extracted from glandular areas. Segmented glandular areas of LCIS were significantly larger, thicker, lower and less variant in intensity, compared to normal areas (Mann-Whitney test, p<0.01). Our models based on data mining algorithms detected LCIS frames at the accuracy rate close to 99%. Our proposed methods may be well incorporated into a further development of computer aided detection (CAD) software for the screening of whole slide images to locate the LCIS areas.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"5 1","pages":"623-624"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80265784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-12DOI: 10.1109/BIBMW.2011.6112397
M. Maleki, Md. Mominul Aziz, L. Rueda
Identification and analysis of types of protein-protein interactions (PPI) is an important problem in molecular biology because of its key role in many biological processes in living cells. In this paper, we focus on obligate and non-obligate complexes, their prediction and analysis. We propose a feature selection scheme called MRMRpro which is based on Minimum Redundancy Maximum Relevance (MRMR) to focus on the most discriminative and relevant properties to distinguish between these two types of complexes. Our prediction approach uses desolvation energies of pairs of atoms or amino acids present in the interfaces of such complexes. Our results on two well-known datasets confirm that MRMRpro leads to significant improvements on performance by finding more relevant features for prediction. Furthermore, the prediction performance of our biologically guided feature selection methods demonstrate that hydrophobic amino acids are more discriminating than hydrophilic and amphipathic amino acids to distinguish between obligate and non-obligate complexes.
{"title":"Analysis of relevant physicochemical properties in obligate and non-obligate protein-protein interactions","authors":"M. Maleki, Md. Mominul Aziz, L. Rueda","doi":"10.1109/BIBMW.2011.6112397","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112397","url":null,"abstract":"Identification and analysis of types of protein-protein interactions (PPI) is an important problem in molecular biology because of its key role in many biological processes in living cells. In this paper, we focus on obligate and non-obligate complexes, their prediction and analysis. We propose a feature selection scheme called MRMRpro which is based on Minimum Redundancy Maximum Relevance (MRMR) to focus on the most discriminative and relevant properties to distinguish between these two types of complexes. Our prediction approach uses desolvation energies of pairs of atoms or amino acids present in the interfaces of such complexes. Our results on two well-known datasets confirm that MRMRpro leads to significant improvements on performance by finding more relevant features for prediction. Furthermore, the prediction performance of our biologically guided feature selection methods demonstrate that hydrophobic amino acids are more discriminating than hydrophilic and amphipathic amino acids to distinguish between obligate and non-obligate complexes.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"12 1","pages":"345-351"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81926538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper is composed based on principal component analysis and wavelet transform method to compare the metabolic networks. We combine 7 centrality topologies of metabolic network to extract a comprehensive center on principal component analysis and construct the original signal based on statistical method. By using the wavelet tool to describe the metabolic network structure, we build the fuzzy function to compare the metabolic network structure between different species. This method above can effectively analyze the structure similarity of different species' metabolic networks, reveal the species-specific of metabolic networks and lay a mathematical foundation for the evolution of metabolic networks. Also it is the first time to use the wavelet analysis method in studying the metabolic networks, and it makes an attempt on a new research direction.
{"title":"Wavelet and PCA for Metabolic Network Comparison","authors":"Yong Luo, Yan Zhao, Lei Cheng","doi":"10.1109/BIBM.2011.27","DOIUrl":"https://doi.org/10.1109/BIBM.2011.27","url":null,"abstract":"This paper is composed based on principal component analysis and wavelet transform method to compare the metabolic networks. We combine 7 centrality topologies of metabolic network to extract a comprehensive center on principal component analysis and construct the original signal based on statistical method. By using the wavelet tool to describe the metabolic network structure, we build the fuzzy function to compare the metabolic network structure between different species. This method above can effectively analyze the structure similarity of different species' metabolic networks, reveal the species-specific of metabolic networks and lay a mathematical foundation for the evolution of metabolic networks. Also it is the first time to use the wavelet analysis method in studying the metabolic networks, and it makes an attempt on a new research direction.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"23 1","pages":"633-638"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82715697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Query expansion based biomedical information retrieval has been studied for over two decades, most of the studies focus only on taking advantage of one vocabulary: MeSH. We propose a completely different approach utilizing an arbitrary number of controlled vocabularies from Metathesaurus. Experiment shows that our ontology based query expansion scheme achieves 8.2% and 17.7% improvement compared with schemes using pseudo relevance feedback query expansion and using no query expansion respectively. The average improvement is 24.8% in comparison to all other existing strategies. Furthermore, we identify that generalized biomedical concepts are the reason for performance degradation.
{"title":"Ontology Graph Based Query Expansion for Biomedical Information Retrieval","authors":"Liang Dong, P. Srimani, J. Wang","doi":"10.1109/BIBM.2011.15","DOIUrl":"https://doi.org/10.1109/BIBM.2011.15","url":null,"abstract":"Query expansion based biomedical information retrieval has been studied for over two decades, most of the studies focus only on taking advantage of one vocabulary: MeSH. We propose a completely different approach utilizing an arbitrary number of controlled vocabularies from Metathesaurus. Experiment shows that our ontology based query expansion scheme achieves 8.2% and 17.7% improvement compared with schemes using pseudo relevance feedback query expansion and using no query expansion respectively. The average improvement is 24.8% in comparison to all other existing strategies. Furthermore, we identify that generalized biomedical concepts are the reason for performance degradation.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"11 1","pages":"488-493"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82556887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-12DOI: 10.1109/BIBMW.2011.6112503
Sachintha Pitigala, Cen Li, S. Seo
Retrieval of the information relevant to one's need from PubMed is becoming increasingly challenging due to its large volume and rapid growth. The traditional information search techniques based on keyword matching are insufficient for large databases such as PubMed. A personalized article retrieval system that is tailored to individual researcher's specific interests and selects only highly relevant articles can be a helpful tool in the field of Bioinformatics. The text classification methods developed in the text mining community have shown good results in differentiating relevant articles from the irrelevant ones. This study compares two text classification methods, Naïve Bayes and Support Vector Machines, in order to study the effectiveness of the two methods on classifying full text articles in the case when only a small set of training data is available. The comparison results show that the Naïve Bayes method is a better choice than Support Vector Machines in building a personalized article retrieval system which can learn (train) from a small set of full text articles.
{"title":"A comparative study of text classification approaches for personalized retrieval in PubMed","authors":"Sachintha Pitigala, Cen Li, S. Seo","doi":"10.1109/BIBMW.2011.6112503","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112503","url":null,"abstract":"Retrieval of the information relevant to one's need from PubMed is becoming increasingly challenging due to its large volume and rapid growth. The traditional information search techniques based on keyword matching are insufficient for large databases such as PubMed. A personalized article retrieval system that is tailored to individual researcher's specific interests and selects only highly relevant articles can be a helpful tool in the field of Bioinformatics. The text classification methods developed in the text mining community have shown good results in differentiating relevant articles from the irrelevant ones. This study compares two text classification methods, Naïve Bayes and Support Vector Machines, in order to study the effectiveness of the two methods on classifying full text articles in the case when only a small set of training data is available. The comparison results show that the Naïve Bayes method is a better choice than Support Vector Machines in building a personalized article retrieval system which can learn (train) from a small set of full text articles.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"67 1","pages":"919-921"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89067841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An important issue in protein-protein interaction network studies is the identification of interaction dynamics. Two factors contribute to the dynamics. One, not all proteins may be expressed in a given cell, and two, competition may exist among multiple proteins for a particular protein domain. Taking into account these two factors, we propose a novel approach to predict protein-protein interaction network dynamics by learning from conflict-sensitive phosphorylation dynamics. We built a training model from conflict-sensitive phosphorylation dynamics. In this model, each node is not an individual protein but a protein-protein pair and is labeled with terms representing conditions in which the interaction should be observed. We mapped the protein pairs in a vector space, built hyper-edges over the interaction nodes, and developed rank-like SVM with Laplacian regularizers for PPI network dynamics prediction. We also employed the standard F1 measure for evaluating the effectiveness of classification results.
{"title":"Learning Condition-Dependent Dynamical PPI Networks from Conflict-Sensitive Phosphorylation Dynamics","authors":"Qiong Cheng, M. Ogihara, Vineet K Gupta","doi":"10.1109/BIBM.2011.127","DOIUrl":"https://doi.org/10.1109/BIBM.2011.127","url":null,"abstract":"An important issue in protein-protein interaction network studies is the identification of interaction dynamics. Two factors contribute to the dynamics. One, not all proteins may be expressed in a given cell, and two, competition may exist among multiple proteins for a particular protein domain. Taking into account these two factors, we propose a novel approach to predict protein-protein interaction network dynamics by learning from conflict-sensitive phosphorylation dynamics. We built a training model from conflict-sensitive phosphorylation dynamics. In this model, each node is not an individual protein but a protein-protein pair and is labeled with terms representing conditions in which the interaction should be observed. We mapped the protein pairs in a vector space, built hyper-edges over the interaction nodes, and developed rank-like SVM with Laplacian regularizers for PPI network dynamics prediction. We also employed the standard F1 measure for evaluating the effectiveness of classification results.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"48 1","pages":"309-312"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87013565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-12DOI: 10.1109/BIBMW.2011.6112419
P. Guzzi, Marianna Milano, P. Veltri, M. Cannataro
Biological data stored in databases can be associated with information (knowledge) such as experiments, properties and functions, response to drugs etc. Such a knowledge is often stored in biological ontologies. Gene Ontology is one of the main resource of biological knowledge providing both a categorization of terms and a source of annotation for genes and proteins. This enables the use of ontology-based methodologies for the analysis of proteins and their functions. One methodology is based on semantic based similarity measures. Recently there is a growing interest in the use of semantic based methodologies to the analysis of protein interaction data such as the prediction of protein complexes based on semantic similarity measures. Despite this interest, there is the need for an assessment of semantic measures as well as a deep study on the impact of the chosen measure in the obtained results. This paper treats the problem of using semantic similarity measure to analyse protein complexes and to improve protein complexes prediction frameworks. Tests have been performed in yeast protein complexes. Results indicate that there exists a bias among measures as well as an higher value of semantic similarity within proteins that participate in the same complex, proving both a possible use of semantic similarity protein complexes prediction and a suggestion in the measure.
{"title":"Using semantic similarity to detect features in yeast protein complexes","authors":"P. Guzzi, Marianna Milano, P. Veltri, M. Cannataro","doi":"10.1109/BIBMW.2011.6112419","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112419","url":null,"abstract":"Biological data stored in databases can be associated with information (knowledge) such as experiments, properties and functions, response to drugs etc. Such a knowledge is often stored in biological ontologies. Gene Ontology is one of the main resource of biological knowledge providing both a categorization of terms and a source of annotation for genes and proteins. This enables the use of ontology-based methodologies for the analysis of proteins and their functions. One methodology is based on semantic based similarity measures. Recently there is a growing interest in the use of semantic based methodologies to the analysis of protein interaction data such as the prediction of protein complexes based on semantic similarity measures. Despite this interest, there is the need for an assessment of semantic measures as well as a deep study on the impact of the chosen measure in the obtained results. This paper treats the problem of using semantic similarity measure to analyse protein complexes and to improve protein complexes prediction frameworks. Tests have been performed in yeast protein complexes. Results indicate that there exists a bias among measures as well as an higher value of semantic similarity within proteins that participate in the same complex, proving both a possible use of semantic similarity protein complexes prediction and a suggestion in the measure.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"119 5 1","pages":"495-502"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88751159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-12DOI: 10.1109/BIBMW.2011.6112427
Sardar Ansari, Ashwin Belle, Kevin Ward, R. Hobson, K. Najarian
Motion artifact reduction is a fundamental part in portable monitoring of physiological signals. Here, the performance of three different motion artifact reduction methods, independent component analysis, least mean square filters and normalized least mean square filters are compared when applied to the impedance plethysmography signal. The results show that the performance of each method depends on the type of motion artifact it is being applied to, and that none of the methods universally performs better than the other ones. As a result, authors suggest that the motion artifact reduction algorithm should be designed based on the nature of the motion artifact.
{"title":"Reduction of periodic motion artifacts from impedance plethysmography","authors":"Sardar Ansari, Ashwin Belle, Kevin Ward, R. Hobson, K. Najarian","doi":"10.1109/BIBMW.2011.6112427","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112427","url":null,"abstract":"Motion artifact reduction is a fundamental part in portable monitoring of physiological signals. Here, the performance of three different motion artifact reduction methods, independent component analysis, least mean square filters and normalized least mean square filters are compared when applied to the impedance plethysmography signal. The results show that the performance of each method depends on the type of motion artifact it is being applied to, and that none of the methods universally performs better than the other ones. As a result, authors suggest that the motion artifact reduction algorithm should be designed based on the nature of the motion artifact.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"20 1","pages":"540-547"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90147574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-11-12DOI: 10.1109/BIBMW.2011.6112468
Zehui He, Chuanjian Lu, A. Ou
This article was to examine the specific contribution of demographic, medical and psychological variables to the Traditional Chinese Medicine (TCM) Syndromes of psoriasis. A cross-sectional survey of psoriasis patients was conducted at 7 hospitals of TCM of different regions. In all, 671 psoriasis patients underwent a clinical assessment including differentiation of TCM syndromes and psoriasis severity (assessed by Psoriasis Area and Severity Index, PASI). Patients also completed questions on demographic data and a quality of life scale (Dermatology Life Quality Index, DLQI). The three main TCM syndromes were included: 354 patients with Wind-heat (52.8%), 161 with Blood-stasis (24.0%), and 156 with Blood-dryness (23.2%). They distributed differently in subgroups of patients with different gender, age, chronic disease, duration of psoriasis, PASI, and DLQI score. The TCM syndromes were close related to demographic and clinical conditions of patients. TCM clinical treatment should consider both characteristics of syndrome and demographic variables of psoriasis.
{"title":"The Traditional Chinese Medicine syndromes of psoriasis in Chinese patients: Contribution of demographic and clinical variables","authors":"Zehui He, Chuanjian Lu, A. Ou","doi":"10.1109/BIBMW.2011.6112468","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112468","url":null,"abstract":"This article was to examine the specific contribution of demographic, medical and psychological variables to the Traditional Chinese Medicine (TCM) Syndromes of psoriasis. A cross-sectional survey of psoriasis patients was conducted at 7 hospitals of TCM of different regions. In all, 671 psoriasis patients underwent a clinical assessment including differentiation of TCM syndromes and psoriasis severity (assessed by Psoriasis Area and Severity Index, PASI). Patients also completed questions on demographic data and a quality of life scale (Dermatology Life Quality Index, DLQI). The three main TCM syndromes were included: 354 patients with Wind-heat (52.8%), 161 with Blood-stasis (24.0%), and 156 with Blood-dryness (23.2%). They distributed differently in subgroups of patients with different gender, age, chronic disease, duration of psoriasis, PASI, and DLQI score. The TCM syndromes were close related to demographic and clinical conditions of patients. TCM clinical treatment should consider both characteristics of syndrome and demographic variables of psoriasis.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"20 1","pages":"765-768"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87906436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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