There is a growing concern to ensure personal information is protected in the emerging information society, and this can be attributed to the increasing incident of identity theft and confidentiality breach. There are also potential risks associated with mishandling personal information in the healthcare sector, for example, medical conditions, which should remain confidential, can be disclosed to unauthorized persons, subsequently leading to negative social and psychological effects on the affected individuals. Many governments and international agencies have developed legislations and guidelines to prevent misuse of personal information by organizations in their jurisdictions. However, there is a challenge in properly integrating the complex nature and interaction of confidentiality concerns in many information systems. This is because the concerns involve multiple interests - the data owner, the data custodian, potential users of the system, as well as government agencies, and they can be conflicting. In addition, the requirements are usually specified in free text form, which can be ambiguous and difficult to translate to software systems. A better understanding of confidentiality requirement properties will assist information system designers and developers in specifying and analyzing the requirements, and ultimately result in good "confidentiality-aware" systems. This research is aimed at developing an approach for improved specification, modelling and analysis of confidentiality requirements. In this paper, we describe the study to identify key confidentiality properties, which will enable precise specification of confidentiality requirements
{"title":"Properties of Confidentiality Requirements","authors":"A. Onabajo, J. Weber","doi":"10.1109/CBMS.2006.133","DOIUrl":"https://doi.org/10.1109/CBMS.2006.133","url":null,"abstract":"There is a growing concern to ensure personal information is protected in the emerging information society, and this can be attributed to the increasing incident of identity theft and confidentiality breach. There are also potential risks associated with mishandling personal information in the healthcare sector, for example, medical conditions, which should remain confidential, can be disclosed to unauthorized persons, subsequently leading to negative social and psychological effects on the affected individuals. Many governments and international agencies have developed legislations and guidelines to prevent misuse of personal information by organizations in their jurisdictions. However, there is a challenge in properly integrating the complex nature and interaction of confidentiality concerns in many information systems. This is because the concerns involve multiple interests - the data owner, the data custodian, potential users of the system, as well as government agencies, and they can be conflicting. In addition, the requirements are usually specified in free text form, which can be ambiguous and difficult to translate to software systems. A better understanding of confidentiality requirement properties will assist information system designers and developers in specifying and analyzing the requirements, and ultimately result in good \"confidentiality-aware\" systems. This research is aimed at developing an approach for improved specification, modelling and analysis of confidentiality requirements. In this paper, we describe the study to identify key confidentiality properties, which will enable precise specification of confidentiality requirements","PeriodicalId":208693,"journal":{"name":"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127695790","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}
P. P. Bržan, M. Verlic, P. Kokol, José L. Sánchez, J. Sigut
We present the results of a supervised approach for identification of follicular lymphomas in microscopy images. A new feature extraction approach is presented. The proposed discriminative features intend to emphasize the distinction among pixels on follicle contour. Additionally those features are used for supervised learning using classificational cellular automata (CCA) approach with the aim to obtain a general decision support model for classification of follicle contours on the microscopy images
{"title":"Identifying Lymphoma in Microscopy Images with Classificational Cellular Automata","authors":"P. P. Bržan, M. Verlic, P. Kokol, José L. Sánchez, J. Sigut","doi":"10.1109/CBMS.2006.97","DOIUrl":"https://doi.org/10.1109/CBMS.2006.97","url":null,"abstract":"We present the results of a supervised approach for identification of follicular lymphomas in microscopy images. A new feature extraction approach is presented. The proposed discriminative features intend to emphasize the distinction among pixels on follicle contour. Additionally those features are used for supervised learning using classificational cellular automata (CCA) approach with the aim to obtain a general decision support model for classification of follicle contours on the microscopy images","PeriodicalId":208693,"journal":{"name":"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126495349","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. Marshall, K. Cairns, F. Kee, M. Moore, A. Hamilton, A. Adgey
This paper describes the development of a model to assess the distribution of response times for mobile volunteers of a public access defibrillation (PAD) scheme in Northern Ireland. Using parameters based on a trial period, the model predicts that a PAD volunteer would arrive before the emergency medical services (EMS) to 18.8% of events to which they are paged in a given year period. This is in agreement with what has actually been observed during the trial period (where volunteers have actually reached 15% of events before the EMS), and thus assisting validation of the model. Results from this model illustrate how ongoing volunteer commitment is key to the success of the scheme
{"title":"A Monte Carlo Simulation Model to Assess Volunteer Response Times in a Public Access Defibrillation Scheme in Northern Ireland","authors":"A. Marshall, K. Cairns, F. Kee, M. Moore, A. Hamilton, A. Adgey","doi":"10.1109/CBMS.2006.19","DOIUrl":"https://doi.org/10.1109/CBMS.2006.19","url":null,"abstract":"This paper describes the development of a model to assess the distribution of response times for mobile volunteers of a public access defibrillation (PAD) scheme in Northern Ireland. Using parameters based on a trial period, the model predicts that a PAD volunteer would arrive before the emergency medical services (EMS) to 18.8% of events to which they are paged in a given year period. This is in agreement with what has actually been observed during the trial period (where volunteers have actually reached 15% of events before the EMS), and thus assisting validation of the model. Results from this model illustrate how ongoing volunteer commitment is key to the success of the scheme","PeriodicalId":208693,"journal":{"name":"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122579419","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}
Frank-Michael Schleif, T. Elssner, M. Kostrzewa, T. Villmann, B. Hammer
We extend the self-organizing map in the variant as proposed by Heskes to a supervised fuzzy classification method. This leads to a robust classifier where efficient learning with fuzzy labeled or partially contradictory data is possible. Further, the integration of labeling into the location of prototypes in a self-organizing map leads to a visualization of those parts of the data relevant for the classification. The method is incorporated in a clinical proteomics toolkit dedicated for biomarker search which allows the necessary preprocessing and further data analysis with additional visualizations
{"title":"Analysis and Visualization of Proteomic Data by Fuzzy Labeled Self-Organizing Maps","authors":"Frank-Michael Schleif, T. Elssner, M. Kostrzewa, T. Villmann, B. Hammer","doi":"10.1109/CBMS.2006.44","DOIUrl":"https://doi.org/10.1109/CBMS.2006.44","url":null,"abstract":"We extend the self-organizing map in the variant as proposed by Heskes to a supervised fuzzy classification method. This leads to a robust classifier where efficient learning with fuzzy labeled or partially contradictory data is possible. Further, the integration of labeling into the location of prototypes in a self-organizing map leads to a visualization of those parts of the data relevant for the classification. The method is incorporated in a clinical proteomics toolkit dedicated for biomarker search which allows the necessary preprocessing and further data analysis with additional visualizations","PeriodicalId":208693,"journal":{"name":"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121434510","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 present the need for risk stratification in the monitoring of cardiac surgical practice and review the frequentist and Bayesian approaches to the problem. Developments in the available databases are described. Enhancements to the Parsonnet and EuroSCORE systems are reviewed. We argue that in the UK, although the use of the Parsonnet system is inappropriate and that the EuroSCORE system is a clear improvement, there are advantages in adopting a system based on a Bayesian model for risk assessment
{"title":"Risk Stratification in Assessing Risk in Coronary Artery Bypass Surgery","authors":"Mike Rees, Jitesh Dineschandra","doi":"10.1109/CBMS.2006.141","DOIUrl":"https://doi.org/10.1109/CBMS.2006.141","url":null,"abstract":"We present the need for risk stratification in the monitoring of cardiac surgical practice and review the frequentist and Bayesian approaches to the problem. Developments in the available databases are described. Enhancements to the Parsonnet and EuroSCORE systems are reviewed. We argue that in the UK, although the use of the Parsonnet system is inappropriate and that the EuroSCORE system is a clear improvement, there are advantages in adopting a system based on a Bayesian model for risk assessment","PeriodicalId":208693,"journal":{"name":"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)","volume":"321 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115866367","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}
M. Barhamgi, D. Benslimane, Pierre-Antoine Champin
Interoperability is a crucial issue in the health care domain. It must be conducted along two tightly-coupled levels: "data" and "application" levels. The former is about bridging together heterogeneous medical data sources. The later is concerned with enabling medical applications to understand each other when they interact through Web services composition. In this paper we present a peer-to-peer framework for ensuring the interoperability along its two levels. Then we present a semantic mediation model dealing with data's "context heterogeneity" between Web services within a composition process
{"title":"A Framework for Data and Web Services Semantic Mediation in Peer-to-Peer Based Medical Information Systems","authors":"M. Barhamgi, D. Benslimane, Pierre-Antoine Champin","doi":"10.1109/CBMS.2006.11","DOIUrl":"https://doi.org/10.1109/CBMS.2006.11","url":null,"abstract":"Interoperability is a crucial issue in the health care domain. It must be conducted along two tightly-coupled levels: \"data\" and \"application\" levels. The former is about bridging together heterogeneous medical data sources. The later is concerned with enabling medical applications to understand each other when they interact through Web services composition. In this paper we present a peer-to-peer framework for ensuring the interoperability along its two levels. Then we present a semantic mediation model dealing with data's \"context heterogeneity\" between Web services within a composition process","PeriodicalId":208693,"journal":{"name":"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116850713","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}
Mykola Pechenizkiy, A. Tsymbal, S. Puuronen, Oleksandr Pechenizkiy
Inductive learning systems have been successfully applied in a number of medical domains. It is generally accepted that the highest accuracy results that an inductive learning system can achieve depend on the quality of data and on the appropriate selection of a learning algorithm for the data. In this paper we analyze the effect of class noise on supervised learning in medical domains. We review the related work on learning from noisy data and propose to use feature extraction as a pre-processing step to diminish the effect of class noise on the learning process. Our experiments with 8 medical datasets show that feature extraction indeed helps to deal with class noise. It clearly results in higher classification accuracy of learnt models without the separate explicit elimination of noisy instances
{"title":"Class Noise and Supervised Learning in Medical Domains: The Effect of Feature Extraction","authors":"Mykola Pechenizkiy, A. Tsymbal, S. Puuronen, Oleksandr Pechenizkiy","doi":"10.1109/CBMS.2006.65","DOIUrl":"https://doi.org/10.1109/CBMS.2006.65","url":null,"abstract":"Inductive learning systems have been successfully applied in a number of medical domains. It is generally accepted that the highest accuracy results that an inductive learning system can achieve depend on the quality of data and on the appropriate selection of a learning algorithm for the data. In this paper we analyze the effect of class noise on supervised learning in medical domains. We review the related work on learning from noisy data and propose to use feature extraction as a pre-processing step to diminish the effect of class noise on the learning process. Our experiments with 8 medical datasets show that feature extraction indeed helps to deal with class noise. It clearly results in higher classification accuracy of learnt models without the separate explicit elimination of noisy instances","PeriodicalId":208693,"journal":{"name":"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117023919","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 describes a methodology for increasing the scope and precision of diagnostic knowledge based (KB) Systems. It has been stated that medical KB systems are either highly specialised, lack accuracy or are just too simple. To resolve this problem of scope we propose the use of a phased approach to diagnosis. The first phase being the querying of a symptoms ontology, to direct diagnostic systems to the most appropriate domain or class reference given input symptoms. Additional symptoms can then be targeted, extracted and analysed with a domain specific set of KB systems. This process allows us to forecast key symptoms, patient characteristics and increase the value of available data in decision making. In addition this approach could allow a system to dynamically correct an inappropriate domain decision. Such an approach also has the potential to be used to build a bridge between existing specialised medical KB systems
{"title":"Symptoms Ontology for Mapping Diagnostic Knowledge Systems","authors":"R. Minchin, F. Porto, C. Vangenot, Sven Hartmann","doi":"10.1109/CBMS.2006.152","DOIUrl":"https://doi.org/10.1109/CBMS.2006.152","url":null,"abstract":"This paper describes a methodology for increasing the scope and precision of diagnostic knowledge based (KB) Systems. It has been stated that medical KB systems are either highly specialised, lack accuracy or are just too simple. To resolve this problem of scope we propose the use of a phased approach to diagnosis. The first phase being the querying of a symptoms ontology, to direct diagnostic systems to the most appropriate domain or class reference given input symptoms. Additional symptoms can then be targeted, extracted and analysed with a domain specific set of KB systems. This process allows us to forecast key symptoms, patient characteristics and increase the value of available data in decision making. In addition this approach could allow a system to dynamically correct an inappropriate domain decision. Such an approach also has the potential to be used to build a bridge between existing specialised medical KB systems","PeriodicalId":208693,"journal":{"name":"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115789009","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}
V. Korampally, S. Bhattacharya, Yuanfang Gao, S. Grant, S. Kleiboeker, K. Gangopadhyay, Jinglu Tan, S. Gangopadhyay
A polymerase chain reaction (PCR) micro-chip with integrated thin film heaters and temperature detectors has been realized on a silicon-SOG-PDMS (poly-di(methyl) siloxane) platform. Accurate temperature sensing and control is important for a PCR reaction. This precludes the placement of the temperature sensor anywhere else but within the PCR chamber which can, in certain microchip designs complicate the fabrication methodology. This paper presents the design and optimal placement of a thin film resistance based temperature detector (RTD) for sensing of temperature response on the bottom of the chip (heater side) and predicting the temperature response on the top of the chip (PCR chamber side). Thermal modeling of the system has been performed using a parametric black-box approach based on the input-output data. From the steady state response of the system, pseudo random binary sequences (PRBS) have been generated and used to excite it. Second and fourth order ARX (auto regressive with exogenous inputs) models have been derived for optimal control and their performances have been compared. Reduction of fabrication complexity in regards to optimal placement of temperature sensor has been proposed
{"title":"Optimization of Fabrication Process for a PDMS-SOG-Silicon Based PCR Micro Chip through System Identification Techniques","authors":"V. Korampally, S. Bhattacharya, Yuanfang Gao, S. Grant, S. Kleiboeker, K. Gangopadhyay, Jinglu Tan, S. Gangopadhyay","doi":"10.1109/CBMS.2006.125","DOIUrl":"https://doi.org/10.1109/CBMS.2006.125","url":null,"abstract":"A polymerase chain reaction (PCR) micro-chip with integrated thin film heaters and temperature detectors has been realized on a silicon-SOG-PDMS (poly-di(methyl) siloxane) platform. Accurate temperature sensing and control is important for a PCR reaction. This precludes the placement of the temperature sensor anywhere else but within the PCR chamber which can, in certain microchip designs complicate the fabrication methodology. This paper presents the design and optimal placement of a thin film resistance based temperature detector (RTD) for sensing of temperature response on the bottom of the chip (heater side) and predicting the temperature response on the top of the chip (PCR chamber side). Thermal modeling of the system has been performed using a parametric black-box approach based on the input-output data. From the steady state response of the system, pseudo random binary sequences (PRBS) have been generated and used to excite it. Second and fourth order ARX (auto regressive with exogenous inputs) models have been derived for optimal control and their performances have been compared. Reduction of fabrication complexity in regards to optimal placement of temperature sensor has been proposed","PeriodicalId":208693,"journal":{"name":"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125346645","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}
Yeshwanth Srinivasan, B. Nutter, S. Mitra, B. Phillips, E. Sinzinger
This paper explores the classification of texture patterns observed in digital images of the cervix. In particular, the problem of identifying and segmenting punctations and mosaic patterns is considered. First, the ability of large scale filter banks in characterizing punctations and mosaic structures is studied using texton models. However, texton-based models fail to consistently classify punctation and mosaic sections obtained from cervix images of different subjects. We present a novel method to segment punctations that combines matched filtering using a Gaussian template with Gaussian mixture models. Features extracted from the objects detected using this novel method on punctation and mosaic sections are shown to provide excellent classification between punctation and mosaicism. Results demonstrate the effectiveness of our approach in detecting punctations and separating punctation sections from mosaic sections
{"title":"Classification of Cervix Lesions Using Filter Bank-Based Texture Mode","authors":"Yeshwanth Srinivasan, B. Nutter, S. Mitra, B. Phillips, E. Sinzinger","doi":"10.1109/CBMS.2006.66","DOIUrl":"https://doi.org/10.1109/CBMS.2006.66","url":null,"abstract":"This paper explores the classification of texture patterns observed in digital images of the cervix. In particular, the problem of identifying and segmenting punctations and mosaic patterns is considered. First, the ability of large scale filter banks in characterizing punctations and mosaic structures is studied using texton models. However, texton-based models fail to consistently classify punctation and mosaic sections obtained from cervix images of different subjects. We present a novel method to segment punctations that combines matched filtering using a Gaussian template with Gaussian mixture models. Features extracted from the objects detected using this novel method on punctation and mosaic sections are shown to provide excellent classification between punctation and mosaicism. Results demonstrate the effectiveness of our approach in detecting punctations and separating punctation sections from mosaic sections","PeriodicalId":208693,"journal":{"name":"19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122670649","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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