Pub Date : 2014-10-01DOI: 10.1109/HealthCom.2014.7001808
C. S. Deolindo, A. Kunicki, F. Brasil, R. Moioli
The anatomical and functional characterization of neuronal assemblies (NAs) is a major challenge in neuroscience. Principal component analysis (PCA) is a widely used method for feature detection, however, when dealing with neuronal data analysis, its limitations have not yet been fully understood. Our work complements previous PCA studies which, in general, characterise NAs based solely on excitatory neuronal interactions. We analysed the performance of PCA in two neglected scenarios: assemblies containing patterns of neural interactions (1) with inhibition and (2) with delays. The analyses considered two types of artificially generated data, one drawn from a traditional Poissonian model, and the other drawn from a latent multivariate Gaussian model; in both models, data from a behaving Wistar rat was used for parameter tuning. Our results highlight scenarios in which neglecting complex interactions between neurons can lead to false conclusions when using PCA to detect NAs. Also, we reinforce the importance of more realistic simulations in the evaluation of neuronal signal processing algorithms.
{"title":"Limitations of principal component analysis as a method to detect neuronal assemblies","authors":"C. S. Deolindo, A. Kunicki, F. Brasil, R. Moioli","doi":"10.1109/HealthCom.2014.7001808","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001808","url":null,"abstract":"The anatomical and functional characterization of neuronal assemblies (NAs) is a major challenge in neuroscience. Principal component analysis (PCA) is a widely used method for feature detection, however, when dealing with neuronal data analysis, its limitations have not yet been fully understood. Our work complements previous PCA studies which, in general, characterise NAs based solely on excitatory neuronal interactions. We analysed the performance of PCA in two neglected scenarios: assemblies containing patterns of neural interactions (1) with inhibition and (2) with delays. The analyses considered two types of artificially generated data, one drawn from a traditional Poissonian model, and the other drawn from a latent multivariate Gaussian model; in both models, data from a behaving Wistar rat was used for parameter tuning. Our results highlight scenarios in which neglecting complex interactions between neurons can lead to false conclusions when using PCA to detect NAs. Also, we reinforce the importance of more realistic simulations in the evaluation of neuronal signal processing algorithms.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127820207","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001821
Carlos Pereira, S. Frade, P. Brandão, R. Correia, Ana Aguiar
E-health has raised a great deal of expectations on improving the quality of health services while simultaneously enabling health services cost reductions. To advance towards those visions, it is imperative to gain the trust of the involved stakeholders, doctors and other medical personnel, patients, families, health care providers and regulators. Even though one critical requirement is interoperability among the various systems involved, currently existing solutions are still vertical silos to a large extent. In this paper, we present an E-health solution that results from the integration of components that comply with rising standards at the various levels of the ICT infrastructure: Machine-to-Machine (M2M) communications for interconnecting devices and services, Health Level 7 (HL7) for communicating with health platforms and openEHR for data semantics, storing and making data available. Concretely, we provide an interoperable and extensible e-health service following these three uprising standards and present the architecture design. We map the service to the various components of the infrastructure building blocks, thus demonstrating how the integration can be successfully accomplished. We are currently developing a prototype solution to be used in a pilot project with 15 elders.
{"title":"Integrating data and network standards into an interoperable e-Health solution","authors":"Carlos Pereira, S. Frade, P. Brandão, R. Correia, Ana Aguiar","doi":"10.1109/HealthCom.2014.7001821","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001821","url":null,"abstract":"E-health has raised a great deal of expectations on improving the quality of health services while simultaneously enabling health services cost reductions. To advance towards those visions, it is imperative to gain the trust of the involved stakeholders, doctors and other medical personnel, patients, families, health care providers and regulators. Even though one critical requirement is interoperability among the various systems involved, currently existing solutions are still vertical silos to a large extent. In this paper, we present an E-health solution that results from the integration of components that comply with rising standards at the various levels of the ICT infrastructure: Machine-to-Machine (M2M) communications for interconnecting devices and services, Health Level 7 (HL7) for communicating with health platforms and openEHR for data semantics, storing and making data available. Concretely, we provide an interoperable and extensible e-health service following these three uprising standards and present the architecture design. We map the service to the various components of the infrastructure building blocks, thus demonstrating how the integration can be successfully accomplished. We are currently developing a prototype solution to be used in a pilot project with 15 elders.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128412653","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001846
R. Rauscher, R. Acharya
Health care is a highly regulated industry in which much value is placed upon privacy and confidentiality. The business of health care, particularly in certain academic environments, requires access to data of varying sensitivities, including information from the public Internet. This paper proposes a VLAN-based architecture for segregating data of varying sensitivities, a list of components that facilitate access to and distillation of data, and a method for one-way promotion of individual nodes from areas of lower security to areas of higher security. The proposed solution is an implementable and pragmatic approach to reducing the risk of data leakage. Quality of experience (QoE) measures of two methods for access (node promotion and porthole-based access) are compared. The node promotion method improves the user-perceived responsiveness of applications over the porthole-based method while reducing flexibility.
{"title":"A network security architecture to reduce the risk of data leakage for health care organizations","authors":"R. Rauscher, R. Acharya","doi":"10.1109/HealthCom.2014.7001846","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001846","url":null,"abstract":"Health care is a highly regulated industry in which much value is placed upon privacy and confidentiality. The business of health care, particularly in certain academic environments, requires access to data of varying sensitivities, including information from the public Internet. This paper proposes a VLAN-based architecture for segregating data of varying sensitivities, a list of components that facilitate access to and distillation of data, and a method for one-way promotion of individual nodes from areas of lower security to areas of higher security. The proposed solution is an implementable and pragmatic approach to reducing the risk of data leakage. Quality of experience (QoE) measures of two methods for access (node promotion and porthole-based access) are compared. The node promotion method improves the user-perceived responsiveness of applications over the porthole-based method while reducing flexibility.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126479449","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 : 2014-10-01DOI: 10.1109/HEALTHCOM.2014.7001839
F. Vitali, A. Amoroso, M. Roccetti, G. Marfia
We present a REST approach to build Health services on the Web. Our proposal originates by the necessity of evolving the current regional health service to accommodate emerging needs that are too complex to accomplish with the current system. The original system extends on the regional scale of Emilia-Romagna, and it is one of the most advanced in Italy. Our architecture inherits some of the basic Web methodologies and techniques to implement an highly scalable and flexible system that is capable to satisfy the current needs and their planned evolutions. Moreover, our approach should allow for an effortlessly addressing of future requirements not foreseen at the moment. Without revolutionizing the current IT infrastructure, our approach introduces a new paradigm that could be implemented by a sophisticated interface to access data and resources.
{"title":"RESTful services for an innovative e-Health infrastructure: A real case study","authors":"F. Vitali, A. Amoroso, M. Roccetti, G. Marfia","doi":"10.1109/HEALTHCOM.2014.7001839","DOIUrl":"https://doi.org/10.1109/HEALTHCOM.2014.7001839","url":null,"abstract":"We present a REST approach to build Health services on the Web. Our proposal originates by the necessity of evolving the current regional health service to accommodate emerging needs that are too complex to accomplish with the current system. The original system extends on the regional scale of Emilia-Romagna, and it is one of the most advanced in Italy. Our architecture inherits some of the basic Web methodologies and techniques to implement an highly scalable and flexible system that is capable to satisfy the current needs and their planned evolutions. Moreover, our approach should allow for an effortlessly addressing of future requirements not foreseen at the moment. Without revolutionizing the current IT infrastructure, our approach introduces a new paradigm that could be implemented by a sophisticated interface to access data and resources.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132876369","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001814
M. Varela, Toni Mäki, J. Merilahti, E. R. Rodriguez, A. Runge
Telemedicine applications provide many opportunities for improving health care in a variety of conditions, in particular for people living in remote or geographically isolated areas without fast access to doctors (“medical deserts”), such as some parts of Finland. In many applications, the technologies used are actually off-the shelf solutions for videoconferencing, in some cases even used in an Over The Top (OTT) fashion over best-effort networks. In these contexts, the quality (both Quality of Experience and Quality of Service) of the whole system can have a greater significance than in other contexts such as entertainment, yet there are no quality monitoring and assessment systems specifically conceived for this purpose. In this paper we present an on-going effort to develop an extensible quality monitoring and benchmarking platform designed with video-based telemedicine applications, and the particular issues associated with them, in mind.
远程医疗的应用为改善各种条件下的卫生保健提供了许多机会，特别是对于生活在偏远或地理上孤立、无法快速就医的地区("医疗沙漠")的人们，例如芬兰的一些地区。在许多应用程序中，所使用的技术实际上是现成的视频会议解决方案，在某些情况下，甚至在尽力而为的网络上以Over the Top (OTT)方式使用。在这些环境中，整个系统的质量(体验质量和服务质量)可能比其他环境(如娱乐)更重要，但没有专门为此目的设想的质量监控和评估系统。在本文中，我们提出了一项正在进行的努力，以开发一个可扩展的质量监测和基准测试平台，该平台设计基于视频的远程医疗应用，以及与之相关的特定问题。
{"title":"QuoTe an extensible platform for QoE monitoring and benchmarking of telemedicine applications","authors":"M. Varela, Toni Mäki, J. Merilahti, E. R. Rodriguez, A. Runge","doi":"10.1109/HealthCom.2014.7001814","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001814","url":null,"abstract":"Telemedicine applications provide many opportunities for improving health care in a variety of conditions, in particular for people living in remote or geographically isolated areas without fast access to doctors (“medical deserts”), such as some parts of Finland. In many applications, the technologies used are actually off-the shelf solutions for videoconferencing, in some cases even used in an Over The Top (OTT) fashion over best-effort networks. In these contexts, the quality (both Quality of Experience and Quality of Service) of the whole system can have a greater significance than in other contexts such as entertainment, yet there are no quality monitoring and assessment systems specifically conceived for this purpose. In this paper we present an on-going effort to develop an extensible quality monitoring and benchmarking platform designed with video-based telemedicine applications, and the particular issues associated with them, in mind.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132364981","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001874
J. L. Seixas, Sylvio Barbon Junior, C. Siqueira, I. Dias, Andre Giovanni Castaldin, A. S. Felinto
This paper presents a seed finding method for region growing segmentation approach using color channel energy in image regions. Instead of using the RGB system separated for each pixel, the proposal uses the energy on each color channel to improve the range of the possible values, then creates a more specific seed to detail different regions. Region size used to calculate energy was adjusted to verify the proposed method. Images used were real wound photos, taken from patients undergoing treatment at the university hospital. Results showed that energy on regions presents enough information to segment, leading to a high percentage of matching with experts marks.
{"title":"Color energy as a seed descriptor for image segmentation with region growing algorithms on skin wound images","authors":"J. L. Seixas, Sylvio Barbon Junior, C. Siqueira, I. Dias, Andre Giovanni Castaldin, A. S. Felinto","doi":"10.1109/HealthCom.2014.7001874","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001874","url":null,"abstract":"This paper presents a seed finding method for region growing segmentation approach using color channel energy in image regions. Instead of using the RGB system separated for each pixel, the proposal uses the energy on each color channel to improve the range of the possible values, then creates a more specific seed to detail different regions. Region size used to calculate energy was adjusted to verify the proposed method. Images used were real wound photos, taken from patients undergoing treatment at the university hospital. Results showed that energy on regions presents enough information to segment, leading to a high percentage of matching with experts marks.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116568722","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001887
C. El-Gemayel, F. Jumel, N. Abouchi, J. Constantin, Doumit Zaouk
A mathematical representation of patient or device is presented by a number of variables which are defined to represent the inputs, outputs and a set of equations describing the interaction of these variables. This paper proposes a global methodology for modeling and simulation medical systems and human body, in order to analyze the performance and the quality of services of all system components. Beginning by defining a new prototype of a global and flexible architecture of mathematical model of human body, that is able to contain required data. Then, describing the simulations representation, by mentions in details the core simulator components, analyzer, and the quality of services indicators. Simulation of mathematical models provides useful tools for diagnosis and analyzing the interactions between efficacy, therapies, side-effects, and outcomes. This will help to better understand the human organism control, to analyze experimental data, to identify and quantify relevant biophysical parameters and to design clinical trials.
{"title":"A global methodology for modeling and simulating medical systems","authors":"C. El-Gemayel, F. Jumel, N. Abouchi, J. Constantin, Doumit Zaouk","doi":"10.1109/HealthCom.2014.7001887","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001887","url":null,"abstract":"A mathematical representation of patient or device is presented by a number of variables which are defined to represent the inputs, outputs and a set of equations describing the interaction of these variables. This paper proposes a global methodology for modeling and simulation medical systems and human body, in order to analyze the performance and the quality of services of all system components. Beginning by defining a new prototype of a global and flexible architecture of mathematical model of human body, that is able to contain required data. Then, describing the simulations representation, by mentions in details the core simulator components, analyzer, and the quality of services indicators. Simulation of mathematical models provides useful tools for diagnosis and analyzing the interactions between efficacy, therapies, side-effects, and outcomes. This will help to better understand the human organism control, to analyze experimental data, to identify and quantify relevant biophysical parameters and to design clinical trials.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124868226","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001885
Lei Song, Yongcai Wang, Jijiang Yang, Jianqiang Li
With the global trend of population aging in industrialized countries, efficient information and communication technologies (ICT) for aiding elders or patients' healthcare have attracted great research attentions. Among these technologies, health state sensing by wearable sensors and mobile phones is an important foundation. It monitors the real-time body states; stores, or sends the result to remote family members or doctors. In this way, it can either help people to pay more attention to the overlooked phenomenon, such as the clue of dangerous disease, or help people to issue panic alert when emergency happens. There are many critical issues in health sensing. First, the sensors must be non-intrusive to people's comfort and safety, while providing good accuracy. At the same time, because of being worn by people, numerous noises posed by body motions must be efficiently processed for reducing false alarming. At last, different health or decease signals generally require different sensing technologies and instrument. To tease out the technology advantages that address these challenges and diversities, this paper presented a survey on the state of the art of health sensing technologies using body sensor networks and mobile phones. It classify related works by their application goals, including i) fall detection, ii) gait analyzing, iii) activity qualification, iv) heart state sensing, and v) sleep sensing. It also conducts summary and comparison of related sensing systems and algorithms, to reveal the development lines in each subarea.
{"title":"Health sensing by wearable sensors and mobile phones: A survey","authors":"Lei Song, Yongcai Wang, Jijiang Yang, Jianqiang Li","doi":"10.1109/HealthCom.2014.7001885","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001885","url":null,"abstract":"With the global trend of population aging in industrialized countries, efficient information and communication technologies (ICT) for aiding elders or patients' healthcare have attracted great research attentions. Among these technologies, health state sensing by wearable sensors and mobile phones is an important foundation. It monitors the real-time body states; stores, or sends the result to remote family members or doctors. In this way, it can either help people to pay more attention to the overlooked phenomenon, such as the clue of dangerous disease, or help people to issue panic alert when emergency happens. There are many critical issues in health sensing. First, the sensors must be non-intrusive to people's comfort and safety, while providing good accuracy. At the same time, because of being worn by people, numerous noises posed by body motions must be efficiently processed for reducing false alarming. At last, different health or decease signals generally require different sensing technologies and instrument. To tease out the technology advantages that address these challenges and diversities, this paper presented a survey on the state of the art of health sensing technologies using body sensor networks and mobile phones. It classify related works by their application goals, including i) fall detection, ii) gait analyzing, iii) activity qualification, iv) heart state sensing, and v) sleep sensing. It also conducts summary and comparison of related sensing systems and algorithms, to reveal the development lines in each subarea.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122136591","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001843
A. Michalas, Nicolae Paladi, C. Gehrmann
As adoption of e-health solutions advances, new computing paradigms - such as cloud computing - bring the potential to improve efficiency in managing medical health records and help reduce costs. However, these opportunities introduce new security risks which can not be ignored. Based on our experience with deploying part of the Swedish electronic health records management system in an infrastructure cloud, we make an overview of major requirements that must be considered when migrating e-health systems to the cloud. Furthermore, we describe in-depth a new attack vector inherent to cloud deployments and present a novel data confidentiality and integrity protection mechanism for infrastructure clouds. This contribution aims to encourage exchange of best practices and lessons learned in migrating public e-health systems to the cloud.
{"title":"Security aspects of e-Health systems migration to the cloud","authors":"A. Michalas, Nicolae Paladi, C. Gehrmann","doi":"10.1109/HealthCom.2014.7001843","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001843","url":null,"abstract":"As adoption of e-health solutions advances, new computing paradigms - such as cloud computing - bring the potential to improve efficiency in managing medical health records and help reduce costs. However, these opportunities introduce new security risks which can not be ignored. Based on our experience with deploying part of the Swedish electronic health records management system in an infrastructure cloud, we make an overview of major requirements that must be considered when migrating e-health systems to the cloud. Furthermore, we describe in-depth a new attack vector inherent to cloud deployments and present a novel data confidentiality and integrity protection mechanism for infrastructure clouds. This contribution aims to encourage exchange of best practices and lessons learned in migrating public e-health systems to the cloud.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129364713","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 : 2014-10-01DOI: 10.1109/HealthCom.2014.7001904
Germanno Teles, C. Oliveira, R. Braga, L. O. M. Andrade, Ronaldo F. Ramos, Paulo Cunha, Mauro Oliveira
This paper proposes the use of Bayesian networks to support the decision-making process in public health systems. In particular, this paper presents LARIISA_Bay, a new component based on Bayesian networks that works together with LARIISA, a context-aware platform to support applications in public health systems. The main goal of the proposed component is to assist teams of health specialists in order to better diagnose diseases through data collected from users of LARIISA. As a case study, we focus on scenarios of dengue fever disease. We classify dengue cases into one of the following levels: normal, grave or emergency. Based on this classification, teams of health specialists can accurately make decisions, for example, to alert a health care agent to visit locations with a high incidence of the disease, to send a team of health specialists when a dengue emergency case has occurred, as well as give technical instructions on how to deal with specific cases. We present a prototype of LARIISA_Bay as well as the corresponding interfaces to support the interactions with the component. We compare the obtained results with real diagnosis of general practitioners. The results presented show the efficiency of the proposed approach.
{"title":"Using Bayesian networks to improve the decision-making process in public health systems","authors":"Germanno Teles, C. Oliveira, R. Braga, L. O. M. Andrade, Ronaldo F. Ramos, Paulo Cunha, Mauro Oliveira","doi":"10.1109/HealthCom.2014.7001904","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001904","url":null,"abstract":"This paper proposes the use of Bayesian networks to support the decision-making process in public health systems. In particular, this paper presents LARIISA_Bay, a new component based on Bayesian networks that works together with LARIISA, a context-aware platform to support applications in public health systems. The main goal of the proposed component is to assist teams of health specialists in order to better diagnose diseases through data collected from users of LARIISA. As a case study, we focus on scenarios of dengue fever disease. We classify dengue cases into one of the following levels: normal, grave or emergency. Based on this classification, teams of health specialists can accurately make decisions, for example, to alert a health care agent to visit locations with a high incidence of the disease, to send a team of health specialists when a dengue emergency case has occurred, as well as give technical instructions on how to deal with specific cases. We present a prototype of LARIISA_Bay as well as the corresponding interfaces to support the interactions with the component. We compare the obtained results with real diagnosis of general practitioners. The results presented show the efficiency of the proposed approach.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127130873","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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