The paper shows how redundancy can be put at work to play a positive role in facilitating the cognitive and coordinative tasks of clinicians in a ward setting. The main requirement to accomplish this positive function is to allow and support clinicians in annotating the clinical record and making correlations between redundant data explicit. We report an observational study we undertook in the design of coordination mechanisms based on a minimal set of meaningful correlations.
{"title":"Supporting Practices of Positive Redundancy for Seamless Care","authors":"F. Cabitza, C. Simone","doi":"10.1109/CBMS.2008.26","DOIUrl":"https://doi.org/10.1109/CBMS.2008.26","url":null,"abstract":"The paper shows how redundancy can be put at work to play a positive role in facilitating the cognitive and coordinative tasks of clinicians in a ward setting. The main requirement to accomplish this positive function is to allow and support clinicians in annotating the clinical record and making correlations between redundant data explicit. We report an observational study we undertook in the design of coordination mechanisms based on a minimal set of meaningful correlations.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"113 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":"124116160","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}
D. Aydogan, M. Hannula, T. Arola, P. Dastidar, J. Hyttinen
In this study, four different dual-tree complex wavelet (DT-CWT) based texture feature extraction methods are developed and compared to segment and classify tissues. Methods that are proposed in this study are based on local energy calculations of sub-bands. Two of the methods use rotation variant texture features and the other two use rotation invariant features. The methods are tested on two texture compositions from the Brodatz texture database and two actual magnetic resonance (MR) images. Results show that there is not a significant difference between using rotation variant or invariant features. On the other hand, for the same Brodatz textures, all DT-CWT based feature extraction methods are competitive with other filtering approaches.
{"title":"Texture Based Classification and Segmentation of Tissues Using DT-CWT Feature Extraction Methods","authors":"D. Aydogan, M. Hannula, T. Arola, P. Dastidar, J. Hyttinen","doi":"10.1109/CBMS.2008.46","DOIUrl":"https://doi.org/10.1109/CBMS.2008.46","url":null,"abstract":"In this study, four different dual-tree complex wavelet (DT-CWT) based texture feature extraction methods are developed and compared to segment and classify tissues. Methods that are proposed in this study are based on local energy calculations of sub-bands. Two of the methods use rotation variant texture features and the other two use rotation invariant features. The methods are tested on two texture compositions from the Brodatz texture database and two actual magnetic resonance (MR) images. Results show that there is not a significant difference between using rotation variant or invariant features. On the other hand, for the same Brodatz textures, all DT-CWT based feature extraction methods are competitive with other filtering approaches.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"49 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":"124026385","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}
Michael C. Lee, L. Böröczky, Kivilcim Sungur-Stasik, Aaron D. Cann, A. Borczuk, S. Kawut, C. Powell
Accurate classification methods are critical in computer-aided diagnosis and other clinical decision support systems. Previous research has studied methods for combining genetic algorithms for feature selection with ensemble classifier systems in an effort to increase classification accuracy. We propose a two-step approach that first uses genetic algorithms to reduce the number of features used to characterize the data, then applies the random subspace method on the remaining features to create a set of diverse but high performing classifiers. These classifiers are combined using ensemble learning techniques to yield a final classification. We demonstrate this approach for computer-aided diagnosis of solitary pulmonary nodules from CT scans, in which the proposed method outperforms several previously described methods.
{"title":"A Two-Step Approach for Feature Selection and Classifier Ensemble Construction in Computer-Aided Diagnosis","authors":"Michael C. Lee, L. Böröczky, Kivilcim Sungur-Stasik, Aaron D. Cann, A. Borczuk, S. Kawut, C. Powell","doi":"10.1109/CBMS.2008.68","DOIUrl":"https://doi.org/10.1109/CBMS.2008.68","url":null,"abstract":"Accurate classification methods are critical in computer-aided diagnosis and other clinical decision support systems. Previous research has studied methods for combining genetic algorithms for feature selection with ensemble classifier systems in an effort to increase classification accuracy. We propose a two-step approach that first uses genetic algorithms to reduce the number of features used to characterize the data, then applies the random subspace method on the remaining features to create a set of diverse but high performing classifiers. These classifiers are combined using ensemble learning techniques to yield a final classification. We demonstrate this approach for computer-aided diagnosis of solitary pulmonary nodules from CT scans, in which the proposed method outperforms several previously described methods.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"59 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":"128467151","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}
Transforming a text-based clinical guideline in a computer-interpretable form is a time-consuming and demanding task due to the various users involved, who have different technical and medical background. In the past, different guideline representation languages and supporting tools have been developed, however, these approaches seldom address the various users' demands and needs in the different steps of the guidelines' life cycle. Our approach is oriented on the guideline life-cycle and takes the requirements and the interactions of the various actors into account to formalize guidelines in a computer-interpretable guideline representation by using a semi-automatic way based on NLP techniques. We analyzed the guideline life-cycle and the roles of the actors to build such a model. This model is prototypical implemented and showed the usefulness and utility for the various users.
{"title":"Easing the Formalization of Clinical Guidelines with a User-tailored, Extensible Agile Model Driven Development (AMDD)","authors":"P. Martini, K. Kaiser, S. Miksch","doi":"10.1109/CBMS.2008.92","DOIUrl":"https://doi.org/10.1109/CBMS.2008.92","url":null,"abstract":"Transforming a text-based clinical guideline in a computer-interpretable form is a time-consuming and demanding task due to the various users involved, who have different technical and medical background. In the past, different guideline representation languages and supporting tools have been developed, however, these approaches seldom address the various users' demands and needs in the different steps of the guidelines' life cycle. Our approach is oriented on the guideline life-cycle and takes the requirements and the interactions of the various actors into account to formalize guidelines in a computer-interpretable guideline representation by using a semi-automatic way based on NLP techniques. We analyzed the guideline life-cycle and the roles of the actors to build such a model. This model is prototypical implemented and showed the usefulness and utility for the various users.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"63 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":"128536100","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}
H. Rajasekaran, Luigi Lo Iacono, P. Hasselmeyer, J. Fingberg, P. Summers, S. Benkner, G. Engelbrecht, A. Arbona, A. Chiarini, C. Friedrich, M. Hofmann-Apitius, K. Kumpf, Bob Moore, P. Bijlenga, J. Iavindrasana, Henning Müller, R. Hose, R. Dunlop, Alejandro F Frangi
This paper presents the system architecture of the @neurIST project, which aims at supporting the research and treatment of cerebral aneurysms by bringing together heterogeneous data, computing and complex processing services. The architecture is generic enough to adapt it to the treatment of other diseases beyond cerebral aneurysms. The paper describes the generic requirements of the system and presents the architecture, applications and middleware technologies used to realise the system and highlights the innovations in @neurIST.
{"title":"@neurIST - Towards a System Architecture for Advanced Disease Management through Integration of Heterogeneous Data, Computing, and Complex Processing Services","authors":"H. Rajasekaran, Luigi Lo Iacono, P. Hasselmeyer, J. Fingberg, P. Summers, S. Benkner, G. Engelbrecht, A. Arbona, A. Chiarini, C. Friedrich, M. Hofmann-Apitius, K. Kumpf, Bob Moore, P. Bijlenga, J. Iavindrasana, Henning Müller, R. Hose, R. Dunlop, Alejandro F Frangi","doi":"10.1109/CBMS.2008.42","DOIUrl":"https://doi.org/10.1109/CBMS.2008.42","url":null,"abstract":"This paper presents the system architecture of the @neurIST project, which aims at supporting the research and treatment of cerebral aneurysms by bringing together heterogeneous data, computing and complex processing services. The architecture is generic enough to adapt it to the treatment of other diseases beyond cerebral aneurysms. The paper describes the generic requirements of the system and presents the architecture, applications and middleware technologies used to realise the system and highlights the innovations in @neurIST.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"282 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":"127514337","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}
Heart disease is one of the most serious medical problems which threaten human life. Now there are several methods for detecting heart disease and ECG (electrocardiogram) signal analysis is one of the typical solutions. The other method such as MCG (magnetocardiogram) is also recommended for heart disease detection. In computer society, the e-Health systems using these diagnosis methods have been developed. However, each diagnosis method has their own weak points and also limitations in system performance according to the increase of data in quantity. Therefore, in order to improve each diagnosis method and conventional e-Health system, we propose and implement a novel integrated-diagnosis system combining grid technologies which is termed as a Physio-Grid system. We present the experimental and evaluation data in order to show our system capability in diagnosis and system performance. The results indicate that the proposed e-Health system can provide the plausible medical services and also it guarantees high reliability and system performance in data management and in diagnosis.
{"title":"Web-Based System for Advanced Heart Disease Identification Using Grid Computing Technology","authors":"Changhee Han, Chan-Hyun Youn, W. Jung","doi":"10.1109/CBMS.2008.106","DOIUrl":"https://doi.org/10.1109/CBMS.2008.106","url":null,"abstract":"Heart disease is one of the most serious medical problems which threaten human life. Now there are several methods for detecting heart disease and ECG (electrocardiogram) signal analysis is one of the typical solutions. The other method such as MCG (magnetocardiogram) is also recommended for heart disease detection. In computer society, the e-Health systems using these diagnosis methods have been developed. However, each diagnosis method has their own weak points and also limitations in system performance according to the increase of data in quantity. Therefore, in order to improve each diagnosis method and conventional e-Health system, we propose and implement a novel integrated-diagnosis system combining grid technologies which is termed as a Physio-Grid system. We present the experimental and evaluation data in order to show our system capability in diagnosis and system performance. The results indicate that the proposed e-Health system can provide the plausible medical services and also it guarantees high reliability and system performance in data management and in diagnosis.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"49 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":"125552162","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 presents the integration of a workflow management system into the VL-e medical software architecture. Workflows are designed with the Taverna workbench, and then executed with the MOTEUR engine on the EGEE grid through the VBrowser, which is the basic front-end for grid-enabled applications in the VL-e medical project. Data management is handled by the virtual file system of the VL-e toolkit. The resulting system provides a high-level interface to execute grid applications.
{"title":"Workflow Integration in VL-e Medical","authors":"T. Glatard, Kamel Boulebiar, S. Olabarriaga","doi":"10.1109/CBMS.2008.114","DOIUrl":"https://doi.org/10.1109/CBMS.2008.114","url":null,"abstract":"This paper presents the integration of a workflow management system into the VL-e medical software architecture. Workflows are designed with the Taverna workbench, and then executed with the MOTEUR engine on the EGEE grid through the VBrowser, which is the basic front-end for grid-enabled applications in the VL-e medical project. Data management is handled by the virtual file system of the VL-e toolkit. The resulting system provides a high-level interface to execute grid applications.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"39 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":"126082398","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}
R. Randell, P. Woodward, Stephanie M. Wilson, J. Galliers
Drawing on data from a multi-site case study of a range of clinical settings, this paper explores the form of nursing handover sheets and the processes through which they are created and updated. We argue that these documents function as both public and private documents, having relevance for the whole ward while also acting as a personal workspace. Such dual functionality needs to be supported by any technology that seeks to provide for the work of handover, if the handover sheet is to continue to act as a space for work, rather than just a repository of information.
{"title":"Public Yet Private: The Status, Durability and Visibility of Handover Sheets","authors":"R. Randell, P. Woodward, Stephanie M. Wilson, J. Galliers","doi":"10.1109/CBMS.2008.52","DOIUrl":"https://doi.org/10.1109/CBMS.2008.52","url":null,"abstract":"Drawing on data from a multi-site case study of a range of clinical settings, this paper explores the form of nursing handover sheets and the processes through which they are created and updated. We argue that these documents function as both public and private documents, having relevance for the whole ward while also acting as a personal workspace. Such dual functionality needs to be supported by any technology that seeks to provide for the work of handover, if the handover sheet is to continue to act as a space for work, rather than just a repository of information.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"56 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":"127015866","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}
In this paper, we proposed an integrated data mining system for patient monitoring with applications on asthma care. In this system, two data mining methods named PBD and PBC are designed for predicting asthma attacks. The main methodology is to extract the significant information of asthma attacks and build classifiers by using users' daily bio-signal records and environmental data. Meanwhile, helpful medical information and suggestions supported by doctors are applied. In this way, the proposed system can predict the chances of asthma attacks and provide patients with the proper medical instructions or health messages. The experimental evaluation results proved that the proposed mechanism is effective and reliable in asthma attack prediction.
{"title":"An Integrated Data Mining System for Patient Monitoring with Applications on Asthma Care","authors":"V. Tseng, Chao-Hui Lee, Jessie Chia-Yu Chen","doi":"10.1109/CBMS.2008.111","DOIUrl":"https://doi.org/10.1109/CBMS.2008.111","url":null,"abstract":"In this paper, we proposed an integrated data mining system for patient monitoring with applications on asthma care. In this system, two data mining methods named PBD and PBC are designed for predicting asthma attacks. The main methodology is to extract the significant information of asthma attacks and build classifiers by using users' daily bio-signal records and environmental data. Meanwhile, helpful medical information and suggestions supported by doctors are applied. In this way, the proposed system can predict the chances of asthma attacks and provide patients with the proper medical instructions or health messages. The experimental evaluation results proved that the proposed mechanism is effective and reliable in asthma attack prediction.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"26 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":"132619079","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 functional motifs composed of several sequential blocks are difficult to find. Current mining methods might individually find each motif block but fail to connect them with large irregular gaps. In this paper we propose a novel method for the efficient extraction of structured motifs from DNA sequences using multi-objective genetic algorithm. The main advantage of our approach is that a large number of nondominated motifs can be obtained by a single run with respect to conflicting objectives: similarity and support maximization and gap minimization. To the best of our knowledge, this is the first effort in this direction. The proposed method can be applied to any data set with a sequential character. Furthermore, it allows any choice of similarity measures for finding motifs. By analyzing the obtained optimal motifs, the decision maker can understand the tradeoff between the objectives. We compare our method with the two well-known structured motif extraction methods, EXMOTIF and RISOTTO. Experimental results on synthetics data set demonstrate that the proposed method exhibits good performance over the other methods in terms of runtime.
{"title":"A Novel Approach to Extract Structured Motifs by Multi-Objective Genetic Algorithm","authors":"Mehmet Kaya, Melikali Güç","doi":"10.1109/CBMS.2008.99","DOIUrl":"https://doi.org/10.1109/CBMS.2008.99","url":null,"abstract":"The functional motifs composed of several sequential blocks are difficult to find. Current mining methods might individually find each motif block but fail to connect them with large irregular gaps. In this paper we propose a novel method for the efficient extraction of structured motifs from DNA sequences using multi-objective genetic algorithm. The main advantage of our approach is that a large number of nondominated motifs can be obtained by a single run with respect to conflicting objectives: similarity and support maximization and gap minimization. To the best of our knowledge, this is the first effort in this direction. The proposed method can be applied to any data set with a sequential character. Furthermore, it allows any choice of similarity measures for finding motifs. By analyzing the obtained optimal motifs, the decision maker can understand the tradeoff between the objectives. We compare our method with the two well-known structured motif extraction methods, EXMOTIF and RISOTTO. Experimental results on synthetics data set demonstrate that the proposed method exhibits good performance over the other methods in terms of runtime.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"28 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":"132739941","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}