A. Depeursinge, J. Iavindrasana, Gilles Cohen, A. Platon, P. Poletti, H. Müller
In this paper, we investigate the influence of the clinical context of high-resolution computed tomography (HRCT) images of the chest on tissue classification. Evaluation of the classification performance is based on high-quality visual data extracted from clinical routine. The clinical attributes with highest information gain ratio show to be relevant and consistent for the classification of lung tissue patterns. A combination of visual and clinical attributes allowed a mean of 93% correct predictions of testing instances among the five classes of lung tissue with optimized support vector machines (SVM), which represents a significant benefit of 8% compared to a pure visually-based classification.
{"title":"Lung Tissue Classification in HRCT Data Integrating the Clinical Context","authors":"A. Depeursinge, J. Iavindrasana, Gilles Cohen, A. Platon, P. Poletti, H. Müller","doi":"10.1109/CBMS.2008.112","DOIUrl":"https://doi.org/10.1109/CBMS.2008.112","url":null,"abstract":"In this paper, we investigate the influence of the clinical context of high-resolution computed tomography (HRCT) images of the chest on tissue classification. Evaluation of the classification performance is based on high-quality visual data extracted from clinical routine. The clinical attributes with highest information gain ratio show to be relevant and consistent for the classification of lung tissue patterns. A combination of visual and clinical attributes allowed a mean of 93% correct predictions of testing instances among the five classes of lung tissue with optimized support vector machines (SVM), which represents a significant benefit of 8% compared to a pure visually-based classification.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132363692","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}
Based upon qualitative work done with former Neonatal Intensive Care Unit parents, we propose a potential user model to estimate the level of stress/anxiety that a parent is experiencing and how information given to such parents should be adjusted to meet their informational and emotional needs.
{"title":"Neonatal Intensive Care Information for Parents An Affective Approach","authors":"Saad Mahamood, Ehud Reiter, C. Mellish","doi":"10.1109/CBMS.2008.37","DOIUrl":"https://doi.org/10.1109/CBMS.2008.37","url":null,"abstract":"Based upon qualitative work done with former Neonatal Intensive Care Unit parents, we propose a potential user model to estimate the level of stress/anxiety that a parent is experiencing and how information given to such parents should be adjusted to meet their informational and emotional needs.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115349349","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}
The education of students in Medical and Nursing Schools is a prime candidate to benefit from the promises of simulation-based learning tools. Well designed computer based systems have been shown to have a dramatic impact on the learning of students. At the same time, the design of these learning tools is still a pain staking task. In this paper, we share our experience at developing and testing a game-based environment for training nursing students.
{"title":"VIMED: Fish-Tank Approach to Nurse Practical Training","authors":"J. Barr, F. Mili, L. Pittiglio, M. Harris","doi":"10.1109/CBMS.2008.128","DOIUrl":"https://doi.org/10.1109/CBMS.2008.128","url":null,"abstract":"The education of students in Medical and Nursing Schools is a prime candidate to benefit from the promises of simulation-based learning tools. Well designed computer based systems have been shown to have a dramatic impact on the learning of students. At the same time, the design of these learning tools is still a pain staking task. In this paper, we share our experience at developing and testing a game-based environment for training nursing students.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121525367","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}
Stavroula Ventoura, Eugenia G. Giannopoulou, E. Manolakos
We present ProtCV (protein clustering and visualization) a new software tool for grouping samples (mass spectra peak-lists) emanating from a high throughput proteomics analysis based on their spectral similarities, and summarizing effectively for the user the clustering results using advanced visualization methods. A unique feature of ProtCV is that it can compare clustering methods applied to the same data set based on several validity in dices to assist the user identify groupings that seem to capture best the underlying structure of the data set. Moreover, ProtCV can assist in formulating hypotheses about the potential role of unidentified proteins in a cluster, identify sets of proteins which act jointly at a specific biological state etc. All these data set mining and exploration operations are very useful for interpreting the results of high throughput MS based proteomics analyses that are commonly used for biomarkers discovery.
protecv (protein clustering and visualization)是一种基于光谱相似性对高通量蛋白质组学分析产生的样品(质谱峰表)进行分组的新软件工具，并使用先进的可视化方法有效地为用户总结聚类结果。ProtCV的一个独特之处在于，它可以根据不同设备的有效性来比较应用于相同数据集的聚类方法，以帮助用户识别似乎最能捕捉数据集底层结构的分组。此外，ProtCV可以帮助制定关于未知蛋白质在集群中的潜在作用的假设，识别在特定生物状态下共同作用的蛋白质集等。所有这些数据集的挖掘和勘探操作对于解释高通量基于质谱的蛋白质组学分析结果非常有用，这些分析通常用于生物标志物的发现。
{"title":"ProtCV: A Tool for Extracting, Visualizing and Validating Protein Clusters Using Mass Spectra Peak-Lists","authors":"Stavroula Ventoura, Eugenia G. Giannopoulou, E. Manolakos","doi":"10.1109/CBMS.2008.95","DOIUrl":"https://doi.org/10.1109/CBMS.2008.95","url":null,"abstract":"We present ProtCV (protein clustering and visualization) a new software tool for grouping samples (mass spectra peak-lists) emanating from a high throughput proteomics analysis based on their spectral similarities, and summarizing effectively for the user the clustering results using advanced visualization methods. A unique feature of ProtCV is that it can compare clustering methods applied to the same data set based on several validity in dices to assist the user identify groupings that seem to capture best the underlying structure of the data set. Moreover, ProtCV can assist in formulating hypotheses about the potential role of unidentified proteins in a cluster, identify sets of proteins which act jointly at a specific biological state etc. All these data set mining and exploration operations are very useful for interpreting the results of high throughput MS based proteomics analyses that are commonly used for biomarkers discovery.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126216849","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}
We propose a new method for measuring the semantic similarity of genes based on path length between their annotation terms in the gene ontology. Our method applies an exponential transfer function to the average path length between two genes to compute their similarity. The non-linear measure ensures that the semantic similarity decreases with distance and proves to be quite competitive when compared to other measures. The advantage of the proposed measure is its simplicity and ease of implementation which gives it a great appeal in this domain. The measure uses only one feature (path length) for computing the similarity between genes. For validation purposes, we computed the similarity of genes from the Saccharomyces genome database (SGD) taking part in various cellular pathways. We analyzed 152 pathways from SGD and compared our similarity results with two of the leading measures. The proposed measure proved to be very competitive in all cases and the clustering results showed that our method is able to surpass the leading methods in certain cases.
{"title":"A New Path Length Measure Based on GO for Gene Similarity with Evaluation using SGD Pathways","authors":"Anurag Nagar, H. Al-Mubaid","doi":"10.1109/CBMS.2008.27","DOIUrl":"https://doi.org/10.1109/CBMS.2008.27","url":null,"abstract":"We propose a new method for measuring the semantic similarity of genes based on path length between their annotation terms in the gene ontology. Our method applies an exponential transfer function to the average path length between two genes to compute their similarity. The non-linear measure ensures that the semantic similarity decreases with distance and proves to be quite competitive when compared to other measures. The advantage of the proposed measure is its simplicity and ease of implementation which gives it a great appeal in this domain. The measure uses only one feature (path length) for computing the similarity between genes. For validation purposes, we computed the similarity of genes from the Saccharomyces genome database (SGD) taking part in various cellular pathways. We analyzed 152 pathways from SGD and compared our similarity results with two of the leading measures. The proposed measure proved to be very competitive in all cases and the clustering results showed that our method is able to surpass the leading methods in certain cases.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"275 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127552291","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}
The paper addresses safety issues involved in making ad hoc interconnections among medical devices in order to assemble more complex medical systems. The main problem is that the systemic view may be easily concealed by nowadays behavioral modeling tools. Missing such a systemic view does not allow to have a precise view of what is being modeled: we propose instead to adopt novel methodological guidelines in developing assembled medical systems, basically by showing how a a clear and unambiguous semantics may be given for any state of the system being modeled, from specification to test phases. Such a state semantics may then be checked against safety axioms by simply visiting the state diagram without the need of resorting to model checking techniques.
{"title":"A State-Based Systemic View of Behavior for Safe Medical Computer Applications","authors":"L. Pazzi, Marco Pradelli","doi":"10.1109/CBMS.2008.94","DOIUrl":"https://doi.org/10.1109/CBMS.2008.94","url":null,"abstract":"The paper addresses safety issues involved in making ad hoc interconnections among medical devices in order to assemble more complex medical systems. The main problem is that the systemic view may be easily concealed by nowadays behavioral modeling tools. Missing such a systemic view does not allow to have a precise view of what is being modeled: we propose instead to adopt novel methodological guidelines in developing assembled medical systems, basically by showing how a a clear and unambiguous semantics may be given for any state of the system being modeled, from specification to test phases. Such a state semantics may then be checked against safety axioms by simply visiting the state diagram without the need of resorting to model checking techniques.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"594 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117074453","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}
A core problem for health information seekers is locating relevant information among the vast amount of online content. Personalization has been suggested as a solution to effective Web information retrieval and also explored in the healthcare context, but then primarily with paper-based or locally available material. In this paper we report on the evaluation of a prototype system, STEPPS, which utilizes electronic patient record data to personalize the retrieval of health information from a variety of online resources, for the purposes of patient education. In a blinded clinician assessment of Web pages retrieved for 27 individual profiles of patients hospitalized in Dutch burn care units, STEPPS performed significantly better than random selection of material.
{"title":"Personalizing Patient Education Using Internet Health Resources and EPR Data: Pilot Evaluation of the STEPPS Prototype System","authors":"P. Doupi, M. V. Wijk, J. V. Wyk, J. Lei","doi":"10.1109/CBMS.2008.105","DOIUrl":"https://doi.org/10.1109/CBMS.2008.105","url":null,"abstract":"A core problem for health information seekers is locating relevant information among the vast amount of online content. Personalization has been suggested as a solution to effective Web information retrieval and also explored in the healthcare context, but then primarily with paper-based or locally available material. In this paper we report on the evaluation of a prototype system, STEPPS, which utilizes electronic patient record data to personalize the retrieval of health information from a variety of online resources, for the purposes of patient education. In a blinded clinician assessment of Web pages retrieved for 27 individual profiles of patients hospitalized in Dutch burn care units, STEPPS performed significantly better than random selection of material.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121973111","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}
Rafael Berlanga Llavori, Ernesto Jiménez-Ruiz, V. Nebot, D. Manset, A. Branson, T. Hauer, R. McClatchey, D. Rogulin, Jetendr Shamdasani, S. Zillner, J. Freund
The integration of heterogeneous biomedical information is one important step towards providing the level of personalization required in the next generation of healthcare provision. In order to provide the computer-based decision support systems needed to access this integrated healthcare information it will be necessary to handle the semantics of (amongst other things) medical protocols. The EC FP6 Health-e-Child project aims to develop an integrated healthcare platform for European paediatrics and decision support tools to access personalized health information. This paper introduces both the integrated data model in the Health-e-Child project and through a case study using the brain tumour protocols it demonstrates the semantic annotation of patient data acquired in the project using UMLS as the primary source of semantic data.
{"title":"Medical Data Integration and the Semantic Annotation of Medical Protocols","authors":"Rafael Berlanga Llavori, Ernesto Jiménez-Ruiz, V. Nebot, D. Manset, A. Branson, T. Hauer, R. McClatchey, D. Rogulin, Jetendr Shamdasani, S. Zillner, J. Freund","doi":"10.1109/CBMS.2008.90","DOIUrl":"https://doi.org/10.1109/CBMS.2008.90","url":null,"abstract":"The integration of heterogeneous biomedical information is one important step towards providing the level of personalization required in the next generation of healthcare provision. In order to provide the computer-based decision support systems needed to access this integrated healthcare information it will be necessary to handle the semantics of (amongst other things) medical protocols. The EC FP6 Health-e-Child project aims to develop an integrated healthcare platform for European paediatrics and decision support tools to access personalized health information. This paper introduces both the integrated data model in the Health-e-Child project and through a case study using the brain tumour protocols it demonstrates the semantic annotation of patient data acquired in the project using UMLS as the primary source of semantic data.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126582951","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 work presents a customizable software framework that supports the analysis of correlations between genotype and phenotype within an integrated database in the context of metabolic disorders. The basis for the examination of relations between genotypes and phenotypes is the information from different life science data sources, merged by a mediator-based system in an integrated database. A graphical Web interface enables user queries to the integrated data and the trace of connections to corresponding data objects in different information domains. As a result of this work, a Web-based prototype of the system is presented. In the context of an example scenario, the framework was used to integrate clinical and molecular biology data for rare metabolic diseases. The framework offers software tools to integrate almost any life science data and to prepare the content for user-specific presentation.
{"title":"A Customizable Framework to Access and Interconnect Clinical Patient Data and Molecular Biology Information","authors":"T. Töpel","doi":"10.1109/CBMS.2008.131","DOIUrl":"https://doi.org/10.1109/CBMS.2008.131","url":null,"abstract":"This work presents a customizable software framework that supports the analysis of correlations between genotype and phenotype within an integrated database in the context of metabolic disorders. The basis for the examination of relations between genotypes and phenotypes is the information from different life science data sources, merged by a mediator-based system in an integrated database. A graphical Web interface enables user queries to the integrated data and the trace of connections to corresponding data objects in different information domains. As a result of this work, a Web-based prototype of the system is presented. In the context of an example scenario, the framework was used to integrate clinical and molecular biology data for rare metabolic diseases. The framework offers software tools to integrate almost any life science data and to prepare the content for user-specific presentation.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133460540","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}
Stroke is the leading cause of adult disability, and training in voluntary movement has been shown to be effective in rebuilding motor skills. We propose an EEG-FES system that can assist in the reconstruction of a closed-loop between motor commands and sensory feedbacks in stroke patients. The system uses event-related desynchronization (ERD) to reflect motor intentions. We did two pilot studies. One focused on extracting clear ERD from healthy subjects who must generally be trained for a few month to extract clear ERD. We also tested the effect of online visual feedback training. The results indicated that for some subjects, but not others, ERD could be extracted in a few days. The other study focused on whether FES (sensory feedback) affects ERD. The results indicated that there was no FES effect (leg stimulation) in leg motor area (Cz) ERD.
{"title":"Electroencephalogram (EEG) and Functional Electrical Stimulation (FES) System for Rehabilitation of Stroke Patients","authors":"Mitsuru Takahashi, M. Gouko, Koji Ito","doi":"10.1109/CBMS.2008.45","DOIUrl":"https://doi.org/10.1109/CBMS.2008.45","url":null,"abstract":"Stroke is the leading cause of adult disability, and training in voluntary movement has been shown to be effective in rebuilding motor skills. We propose an EEG-FES system that can assist in the reconstruction of a closed-loop between motor commands and sensory feedbacks in stroke patients. The system uses event-related desynchronization (ERD) to reflect motor intentions. We did two pilot studies. One focused on extracting clear ERD from healthy subjects who must generally be trained for a few month to extract clear ERD. We also tested the effect of online visual feedback training. The results indicated that for some subjects, but not others, ERD could be extracted in a few days. The other study focused on whether FES (sensory feedback) affects ERD. The results indicated that there was no FES effect (leg stimulation) in leg motor area (Cz) ERD.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129698028","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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