Pub Date : 2011-11-12DOI: 10.1109/BIBMW.2011.6112352
F. Abate, A. Acquaviva, E. Ficarra, Giulia Paciello, E. Macii, A. Ferrarini, M. Delledonne, S. Soverini, G. Martinelli
Next generation sequencing plays a key role in the detection of structural variations. Chimeric transcripts are relevant examples of such variations, as they are involved in several diseases. In this work, we propose an effective methodology for the detection of fused transcripts in RNA-Seq paired-end data. The proposed methodology is based on an accurate fusion model implemented by a set of filters reducing the impact of artifacts. Moreover, the methodology accounts for transcripts consistently expressing in the sample under study even if they are not annotated. The effectiveness of the proposed solution has been experimentally validated on of Chronic Myelogenous Leukemia (CML) samples, providing both the genes involved in the fusion and the exact chimeric sequence.
{"title":"A novel framework for chimeric transcript detection based on accurate gene fusion model","authors":"F. Abate, A. Acquaviva, E. Ficarra, Giulia Paciello, E. Macii, A. Ferrarini, M. Delledonne, S. Soverini, G. Martinelli","doi":"10.1109/BIBMW.2011.6112352","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112352","url":null,"abstract":"Next generation sequencing plays a key role in the detection of structural variations. Chimeric transcripts are relevant examples of such variations, as they are involved in several diseases. In this work, we propose an effective methodology for the detection of fused transcripts in RNA-Seq paired-end data. The proposed methodology is based on an accurate fusion model implemented by a set of filters reducing the impact of artifacts. Moreover, the methodology accounts for transcripts consistently expressing in the sample under study even if they are not annotated. The effectiveness of the proposed solution has been experimentally validated on of Chronic Myelogenous Leukemia (CML) samples, providing both the genes involved in the fusion and the exact chimeric sequence.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"11 1","pages":"34-41"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87757363","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.2011.6112541
James Karnia, K. Delfino, M. Villamil, G. Caetano-Anollés, S. Rodriguez-Zas
Gene expression microarray experiments can be used to infer the topology of co-expression networks between genes in the immune-system pathways. Immune-system pathways are highly dimensional, including numerous gene nodes and edges connecting nodes. A bioinformatics strategy to infer and confirm gene co-expression networks was developed and applied to two major immune-system pathways. In total, 182 and 356 co-expression profiles between pairs of genes were identified in the NOD-like and B-cell receptor signaling pathways. The distinct distribution of the sign of the relationships among the pathways offered additional insights into the network.
{"title":"Integration of statistical models and visualization tools to characterize microRNA networks influencing cancer","authors":"James Karnia, K. Delfino, M. Villamil, G. Caetano-Anollés, S. Rodriguez-Zas","doi":"10.1109/BIBMW.2011.6112541","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112541","url":null,"abstract":"Gene expression microarray experiments can be used to infer the topology of co-expression networks between genes in the immune-system pathways. Immune-system pathways are highly dimensional, including numerous gene nodes and edges connecting nodes. A bioinformatics strategy to infer and confirm gene co-expression networks was developed and applied to two major immune-system pathways. In total, 182 and 356 co-expression profiles between pairs of genes were identified in the NOD-like and B-cell receptor signaling pathways. The distinct distribution of the sign of the relationships among the pathways offered additional insights into the network.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"28 1","pages":"1009-1011"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85877099","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.2011.6112436
Siddharth Pandey, M. Kane, John A. Springer
Scientists studying organisms face challenges when identifying related literature that pertains to the organisms under investigation. This is due to the presence of vast biomedical literature and the limitations of existing automated mechanisms to search through the published literature for the pertinent information. This study proposes the use of the Genomic Literature Area Sequence Search (GLASS) tool to search through the existing literature for relevant information and thus to facilitate information reuse as well as to provide quicker access to the information that otherwise often requires manual, time intensive intervention. By indexing the literature content and then distributing the indexed data across a cluster to provide a faster and robust search process, the application searches through the literature for DNA sequences requested by the user.
研究生物的科学家在识别与所研究的生物相关的文献时面临着挑战。这是由于大量生物医学文献的存在和现有的自动化机制的局限性，无法通过已发表的文献搜索相关信息。本研究建议使用基因组文献区域序列搜索(Genomic Literature Area Sequence Search, GLASS)工具在现有文献中搜索相关信息，从而促进信息重用，并提供更快的信息访问，否则通常需要人工、耗时的干预。通过对文献内容建立索引，然后将索引后的数据分布到集群中，以提供更快、更健壮的搜索过程，应用程序在文献中搜索用户请求的DNA序列。
{"title":"GLASS: Genomic Literature Area Sequence Search","authors":"Siddharth Pandey, M. Kane, John A. Springer","doi":"10.1109/BIBMW.2011.6112436","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112436","url":null,"abstract":"Scientists studying organisms face challenges when identifying related literature that pertains to the organisms under investigation. This is due to the presence of vast biomedical literature and the limitations of existing automated mechanisms to search through the published literature for the pertinent information. This study proposes the use of the Genomic Literature Area Sequence Search (GLASS) tool to search through the existing literature for relevant information and thus to facilitate information reuse as well as to provide quicker access to the information that otherwise often requires manual, time intensive intervention. By indexing the literature content and then distributing the indexed data across a cluster to provide a faster and robust search process, the application searches through the literature for DNA sequences requested by the user.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"4 1","pages":"598-599"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87525782","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.2011.6112535
M. Grasso, Darshana Dalvi, Soma Das, Matthew Gately, Vlad Korolev, Y. Yesha
Type 2 diabetes and coronary artery disease are commonly occurring polygenic diseases, which are responsible for significant morbidity and mortality. The identification of people at risk for these conditions has historically been based on clinical factors alone. Advances in genetics have raised the hope that genetic testing may aid in disease prediction, treatment, and prevention. Although intuitive, the addition of genetic information to increase the accuracy of disease prediction remains an unproven hypothesis. We present an overview of genetic issues involved in polygenic diseases, and summarize ongoing efforts to use this information for disease prediction.
{"title":"Genetic information for chronic disease prediction","authors":"M. Grasso, Darshana Dalvi, Soma Das, Matthew Gately, Vlad Korolev, Y. Yesha","doi":"10.1109/BIBMW.2011.6112535","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112535","url":null,"abstract":"Type 2 diabetes and coronary artery disease are commonly occurring polygenic diseases, which are responsible for significant morbidity and mortality. The identification of people at risk for these conditions has historically been based on clinical factors alone. Advances in genetics have raised the hope that genetic testing may aid in disease prediction, treatment, and prevention. Although intuitive, the addition of genetic information to increase the accuracy of disease prediction remains an unproven hypothesis. We present an overview of genetic issues involved in polygenic diseases, and summarize ongoing efforts to use this information for disease prediction.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"53 1","pages":"997-997"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83571974","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.2011.6112470
N. Tian, Bing Xi, Bi-Ying Su, Ri-Xin Chen
Objective : Study the infrared radiation characteristic of heat-sensitive acupoints in bronchial asthma. Method: Apply Thermal Texture Mapping System (TSI-21) to study the infrared radiation characteristic of heat-sensitive acupoints on the body surfaces of 54 bronchial asthma patients. Set control areas on the back of the patient and 4 separate control points, each in the width of 3cm respectively at the left, right, upper and lower section of the acupoint. Apply two observation indicators, respectively the absolute infrared radiant intensity (temperature) and relative infrared radiant intensity (differential value between the radiant intensity of the control point and the overall radiant intensity), and compare the value of infrared radiant intensity measured at heat-sensitive acupoints and control points/areas. Result: The average temperature of heat-sensitive acupoints in 54 bronchial asthma patients measured at 31.15°C, which indicated that the differential value between the radiant intensity of heat-sensitive acupoints and the overall radiant intensity was significant (P<0.05); Mean whilst, the difference between the temperature of heat-sensitive acupoint and control point was not significant (P> 0.05); however, the difference between the average temperature of heat-sensitive acupoints and the average temperature of the control points on the back of the patient was significant (P<0.05). Conclusion : Heat-sensitive acupoints are featured with high-level infrared radiant intensity; therefore, a certain area of enhanced infrared radiant intensity can be formed around the heat-sensitive acupoint.
{"title":"Study on infrared radiation characteristic of heat-sensitive acupoints in bronchial asthma","authors":"N. Tian, Bing Xi, Bi-Ying Su, Ri-Xin Chen","doi":"10.1109/BIBMW.2011.6112470","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112470","url":null,"abstract":"Objective : Study the infrared radiation characteristic of heat-sensitive acupoints in bronchial asthma. Method: Apply Thermal Texture Mapping System (TSI-21) to study the infrared radiation characteristic of heat-sensitive acupoints on the body surfaces of 54 bronchial asthma patients. Set control areas on the back of the patient and 4 separate control points, each in the width of 3cm respectively at the left, right, upper and lower section of the acupoint. Apply two observation indicators, respectively the absolute infrared radiant intensity (temperature) and relative infrared radiant intensity (differential value between the radiant intensity of the control point and the overall radiant intensity), and compare the value of infrared radiant intensity measured at heat-sensitive acupoints and control points/areas. Result: The average temperature of heat-sensitive acupoints in 54 bronchial asthma patients measured at 31.15°C, which indicated that the differential value between the radiant intensity of heat-sensitive acupoints and the overall radiant intensity was significant (P<0.05); Mean whilst, the difference between the temperature of heat-sensitive acupoint and control point was not significant (P> 0.05); however, the difference between the average temperature of heat-sensitive acupoints and the average temperature of the control points on the back of the patient was significant (P<0.05). Conclusion : Heat-sensitive acupoints are featured with high-level infrared radiant intensity; therefore, a certain area of enhanced infrared radiant intensity can be formed around the heat-sensitive acupoint.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"91 1","pages":"773-777"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83917196","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}
Message RNA (mRNA) is the template for protein synthesis. It carries information from DNA in the nucleus to the ribosome sites of protein synthesis in the cell. The turnover process of mRNA is a chemical event with multiple small step reactions, and the degradation of mRNA molecules is an important step in gene expression. A number of mathematical models have been proposed to study the dynamics of mRNA turnover, ranging from a one-step first order reaction model to the linear multi component models. Although the linear multi component models provide detailed dynamics of mRNA degradation, the simple first-order reaction model has been widely used in mathematical modeling of genetic regulatory networks. To illustrate the difference between these models, we first considered a stochastic model based on the multi component model. Then a simpler linear chain stochastic model was proposed to approximate the linear multi component model. We also discussed the delayed one-step reaction models with different types of time delay, including the constant delay, exponentially distributed delay and Erlang distributed delay. The comparison study suggested that the one-step reaction models failed to realize the dynamics of mRNA turnover accurately. Therefore more sophisticated one-step reaction models are needed to study the dynamics of mRNA degradation.
{"title":"Stochastic Models for Studying the Degradation of mRNA Molecules","authors":"Tianhai Tian","doi":"10.1109/BIBM.2011.100","DOIUrl":"https://doi.org/10.1109/BIBM.2011.100","url":null,"abstract":"Message RNA (mRNA) is the template for protein synthesis. It carries information from DNA in the nucleus to the ribosome sites of protein synthesis in the cell. The turnover process of mRNA is a chemical event with multiple small step reactions, and the degradation of mRNA molecules is an important step in gene expression. A number of mathematical models have been proposed to study the dynamics of mRNA turnover, ranging from a one-step first order reaction model to the linear multi component models. Although the linear multi component models provide detailed dynamics of mRNA degradation, the simple first-order reaction model has been widely used in mathematical modeling of genetic regulatory networks. To illustrate the difference between these models, we first considered a stochastic model based on the multi component model. Then a simpler linear chain stochastic model was proposed to approximate the linear multi component model. We also discussed the delayed one-step reaction models with different types of time delay, including the constant delay, exponentially distributed delay and Erlang distributed delay. The comparison study suggested that the one-step reaction models failed to realize the dynamics of mRNA turnover accurately. Therefore more sophisticated one-step reaction models are needed to study the dynamics of mRNA degradation.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"298 1","pages":"167-172"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77235916","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}
Computer-aided histological image classification systems are important for making objective and timely cancer diagnostic decisions. These systems use combinations of image features that quantify a variety of image properties. Because researchers tend to validate their diagnostic systems on specific cancer endpoints, it is difficult to predict which image features will perform well given a new cancer endpoint. In this paper, we define a comprehensive set of common image features (consisting of 12 distinct feature subsets) that quantify a variety of image properties. We use a data-mining approach to determine which feature subsets and image properties emerge as part of an "optimal" diagnostic model when applied to specific cancer endpoints. Our goal is to assess the performance of such comprehensive image feature sets for application to a wide variety of diagnostic problems. We perform this study on 12 endpoints including 6 renal tumor subtype endpoints and 6 renal cancer grade endpoints.
{"title":"Histological Image Feature Mining Reveals Emergent Diagnostic Properties for Renal Cancer","authors":"S. Kothari, J. Phan, A. Young, May D. Wang","doi":"10.1109/BIBM.2011.112","DOIUrl":"https://doi.org/10.1109/BIBM.2011.112","url":null,"abstract":"Computer-aided histological image classification systems are important for making objective and timely cancer diagnostic decisions. These systems use combinations of image features that quantify a variety of image properties. Because researchers tend to validate their diagnostic systems on specific cancer endpoints, it is difficult to predict which image features will perform well given a new cancer endpoint. In this paper, we define a comprehensive set of common image features (consisting of 12 distinct feature subsets) that quantify a variety of image properties. We use a data-mining approach to determine which feature subsets and image properties emerge as part of an \"optimal\" diagnostic model when applied to specific cancer endpoints. Our goal is to assess the performance of such comprehensive image feature sets for application to a wide variety of diagnostic problems. We perform this study on 12 endpoints including 6 renal tumor subtype endpoints and 6 renal cancer grade endpoints.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"28 1","pages":"422-425"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77604019","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.2011.6112392
Jyh-Jong Tsay, S. Su
The protein is the main working machine of the cells. It has various catalytic and physiological functions. Its function comes from the conformation of the protein and catalytic activity. The conformation is formed by the permutations of amino-acids, and the permutation of the amino-acids, accomplishes the multiplicity of the protein. A great challenge in computational molecular biology is to predicate the protein native structure from its primary amino acid sequence. It is not difficult to obtain protein sequences. However to determine protein structure is not an easy task by current technologies. There is a large gap between them. Therefore, more research is needed to fill the gap. This study proposed a memetic algorithm for protein structure prediction in FCC lattice HP model. The experiment result shows that the MA method proposed in this study can retain the merits of the Genetic algorithm which is good at solve combinatorial problem. It can also increase the efficacy effectively.
{"title":"Ab initio protein structure prediction based on memetic algorithm and 3D FCC lattice model","authors":"Jyh-Jong Tsay, S. Su","doi":"10.1109/BIBMW.2011.6112392","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112392","url":null,"abstract":"The protein is the main working machine of the cells. It has various catalytic and physiological functions. Its function comes from the conformation of the protein and catalytic activity. The conformation is formed by the permutations of amino-acids, and the permutation of the amino-acids, accomplishes the multiplicity of the protein. A great challenge in computational molecular biology is to predicate the protein native structure from its primary amino acid sequence. It is not difficult to obtain protein sequences. However to determine protein structure is not an easy task by current technologies. There is a large gap between them. Therefore, more research is needed to fill the gap. This study proposed a memetic algorithm for protein structure prediction in FCC lattice HP model. The experiment result shows that the MA method proposed in this study can retain the merits of the Genetic algorithm which is good at solve combinatorial problem. It can also increase the efficacy effectively.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"98 3","pages":"315-318"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91448440","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.2011.6112472
Yi Luo, Ji-qiang Li, D. Zheng, Zhan-Peng Tan, Hong Zhou, Q. Deng, Yuntao Liu, A. Ou, Jian Yin
This study is to explore effect and significance of data mining technology (DMT) used in excavating prevention and treatment experience of infectious diseases from famous herbalist doctors (FHDs). DMT methods such as cluster analysis and association rules was applied to the study on FHDs literature on preventing and treating influenza, dysentery, tuberculosis, viral hepatitis and other infectious diseases in order to excavate the inner rules and refine the regular understanding. The result shows that cluster analysis is helpful to summarize the common understanding of experience including concept of syndrome differentiation, regulation of diagnosis and treatment, prescription characteristic, which based on FHDs' prevention and treatment of influenza (including A H1N1), viral hepatitis and other infectious diseases. Association rules greatly contributed to the judgment of relationship between etiology, syndrome, symptoms and herbal prescription of infectious diseases. In conclusion, DMT provides technical support for concise and inheritance of academic thought which originates from FHDs. DMT is of high application value in research of experience of FHDs and relevant literature, and is worth further discussion.
{"title":"Application of data mining technology in excavating prevention and treatment experience of infectious diseases from famous herbalist doctors","authors":"Yi Luo, Ji-qiang Li, D. Zheng, Zhan-Peng Tan, Hong Zhou, Q. Deng, Yuntao Liu, A. Ou, Jian Yin","doi":"10.1109/BIBMW.2011.6112472","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112472","url":null,"abstract":"This study is to explore effect and significance of data mining technology (DMT) used in excavating prevention and treatment experience of infectious diseases from famous herbalist doctors (FHDs). DMT methods such as cluster analysis and association rules was applied to the study on FHDs literature on preventing and treating influenza, dysentery, tuberculosis, viral hepatitis and other infectious diseases in order to excavate the inner rules and refine the regular understanding. The result shows that cluster analysis is helpful to summarize the common understanding of experience including concept of syndrome differentiation, regulation of diagnosis and treatment, prescription characteristic, which based on FHDs' prevention and treatment of influenza (including A H1N1), viral hepatitis and other infectious diseases. Association rules greatly contributed to the judgment of relationship between etiology, syndrome, symptoms and herbal prescription of infectious diseases. In conclusion, DMT provides technical support for concise and inheritance of academic thought which originates from FHDs. DMT is of high application value in research of experience of FHDs and relevant literature, and is worth further discussion.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"31 6","pages":"784-790"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91453361","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.2011.6112490
Cao Yemin, Zhang Haowei, Xu Hongtao, Xi Jiuyi, Zhu Xunsheng, Gu Zheng
Xi Jiuyi, born in 1923, is a famous expert on peripheral vascular diseases. He has been engaged in scientific research and clinical teaching over 60 years and cured of the countless patients. He has decided the five clinical classifications of diabetic foot (DF) and got outstanding curative effects. Following the medical practice of Professor Xi and using engineering technology, we collect symptoms, signs, tongue and pulse condition of 103 cases. Then we use fuzzy C-means clustering method by calculation iterative with the information of 103 cases. The result shows the average accuracy rate is 86.41% similarity with Professor Xi's results of clinical classification. With the expansion of the samples, we believe a higher accuracy rate can be reached. We can draw a conclusion that fuzzy C-means clustering method can reflect the Professor Xi's idea of DF clinic classification, thus inherit the academic ideas of Xi effectively.
{"title":"Research on the clinical classification of Xi clan diabetic foot using fuzzy C-means clustering method","authors":"Cao Yemin, Zhang Haowei, Xu Hongtao, Xi Jiuyi, Zhu Xunsheng, Gu Zheng","doi":"10.1109/BIBMW.2011.6112490","DOIUrl":"https://doi.org/10.1109/BIBMW.2011.6112490","url":null,"abstract":"Xi Jiuyi, born in 1923, is a famous expert on peripheral vascular diseases. He has been engaged in scientific research and clinical teaching over 60 years and cured of the countless patients. He has decided the five clinical classifications of diabetic foot (DF) and got outstanding curative effects. Following the medical practice of Professor Xi and using engineering technology, we collect symptoms, signs, tongue and pulse condition of 103 cases. Then we use fuzzy C-means clustering method by calculation iterative with the information of 103 cases. The result shows the average accuracy rate is 86.41% similarity with Professor Xi's results of clinical classification. With the expansion of the samples, we believe a higher accuracy rate can be reached. We can draw a conclusion that fuzzy C-means clustering method can reflect the Professor Xi's idea of DF clinic classification, thus inherit the academic ideas of Xi effectively.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"162 ","pages":"881-885"},"PeriodicalIF":0.0,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91454893","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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