The Experts below are selected from a list of 231 Experts worldwide ranked by ideXlab platform

Naranker Dulay - One of the best experts on this subject based on the ideXlab platform.

  • A Consent-based Workflow System for Healthcare Systems
    2015
    Co-Authors: Giovanni Russello, Changyu Dong, Naranker Dulay
    Abstract:

    In this paper, we describe a new framework for healthcare systems where patients are able to control the disclosure of their Medical data. In our framework, the patient's consent has a pivotal role in granting or removing access rights to subjects accessing patient's Medical data. Depending on the context in which the access is being executed, different consent policies can be applied. Context is expressed in terms of workflows. The execution of a task in a given workflow carries the necessary information to infer whether the consent can be implicitly retrieved or should be explicitly requested from a patient. However, patients are always able to enforce their own decisions and withdraw consent if necessary. Additionally, the use of workflows enables us to apply the need-to-know principle. Even when the patient's consent is obtained, a subject should access Medical data only if it is required by the actual situation. For example, if the subject is assigned to the execution of a Medical diagnosis workflow requiring access to the patient's Medical record. We also provide a complex Medical Case Study to highlight the design principles behind our framework. Finally, the implementation of the framework is outlined.

  • Consent-Based Workflows for Healthcare Management
    2008 IEEE Workshop on Policies for Distributed Systems and Networks, 2008
    Co-Authors: Giovanni Russello, Changyu Dong, Naranker Dulay
    Abstract:

    In this paper, we describe a new framework for healthcare systems where patients are able to control the disclosure of their Medical data. In our framework, the patient's consent has a pivotal role in granting or removing access rights to subjects accessing patient's Medical data. Depending on the context in which the access is being executed, different consent policies can be applied. Context is expressed in terms of workflows. The execution of a task in a given workflow carries the necessary information to infer whether the consent can be implicitly retrieved or should be explicitly requested from a patient. However, patients are always able to enforce their own decisions and withdraw consent if necessary. Additionally, the use of workflows enables us to apply the need-to-know principle. Even when the patient's consent is obtained, a subject should access Medical data only if it is required by the actual situation. For example, if the subject is assigned to the execution of a Medical diagnosis workflow requiring access to the patient's Medical record. We also provide a complex Medical Case Study to highlight the design principles behind our framework. Finally, the implementation of the framework is outlined.

  • POLICY - Consent-Based Workflows for Healthcare Management
    2008 IEEE Workshop on Policies for Distributed Systems and Networks, 2008
    Co-Authors: Giovanni Russello, Changyu Dong, Naranker Dulay
    Abstract:

    In this paper, we describe a new framework for healthcare systems where patients are able to control the disclosure of their Medical data. In our framework, the patient's consent has a pivotal role in granting or removing access rights to subjects accessing patient's Medical data. Depending on the context in which the access is being executed, different consent policies can be applied. Context is expressed in terms of workflows. The execution of a task in a given workflow carries the necessary information to infer whether the consent can be implicitly retrieved or should be explicitly requested from a patient. However, patients are always able to enforce their own decisions and withdraw consent if necessary. Additionally, the use of workflows enables us to apply the need-to-know principle. Even when the patient's consent is obtained, a subject should access Medical data only if it is required by the actual situation. For example, if the subject is assigned to the execution of a Medical diagnosis workflow requiring access to the patient's Medical record. We also provide a complex Medical Case Study to highlight the design principles behind our framework. Finally, the implementation of the framework is outlined.

  • A Workflow-Based Access Control Framework for e-Health Applications
    22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008), 2008
    Co-Authors: Giovanni Russello, Changyu Dong, Naranker Dulay
    Abstract:

    In this paper, we present a framework where access rights are provided to entities on the basis of the actual task that the entities must fulfill as part of their duties. For capturing the requirements of entities' duties we use the notion of workflow. Our main aim is to provide an access control mechanism that is able to balance the competing goals of flexibility and security. As the main beneficiary of our approach we consider e-Health Applications, where flexibility and security are major requirements. We also provide an implementation of a Medical Case Study to illustrate the framework.

  • AINA Workshops - A Workflow-Based Access Control Framework for e-Health Applications
    22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008), 2008
    Co-Authors: Giovanni Russello, Changyu Dong, Naranker Dulay
    Abstract:

    In this paper, we present a framework where access rights are provided to entities on the basis of the actual task that the entities must fulfill as part of their duties. For capturing the requirements of entities' duties we use the notion of workflow. Our main aim is to provide an access control mechanism that is able to balance the competing goals of flexibility and security. As the main beneficiary of our approach we consider e-Health Applications, where flexibility and security are major requirements. We also provide an implementation of a Medical Case Study to illustrate the framework.

Sandeep K. S. Gupta - One of the best experts on this subject based on the ideXlab platform.

  • Spatio-temporal hybrid automata for safe cyber-physical systems: A Medical Case Study
    2013 ACM IEEE International Conference on Cyber-Physical Systems (ICCPS), 2013
    Co-Authors: Ayan Banerjee, Sandeep K. S. Gupta
    Abstract:

    Interactions between the computing units and the physical environment in Cyber-Physical Systems (CPSes) are considered to verify safety properties, i.e. ensuring the un-intentional side-effects of cyber-physical interactions are within desired limits. A Linear 1 space dimension Spatio-Temporal Hybrid Automata (LlSTHA) is defined to capture the effects of the interactions, in both time and space. Aggregate effects of interactions due to concurrent operations in the computing entities are expressed as a set of interdependent partial differential equations associated with dedicated modes of the LlSTHA model. A time and space bound LlSTHA reachability analysis algorithm is proposed for safety verification, which provides reachable states of the L1STHA with an arbitrary accuracy ϵ. The runtime of the algorithm depends on the requested accuracy. The usage of the LlSTHA modeling and analysis is demonstrated for Medical CPSes such as infusion pumps.

  • spatio temporal hybrid automata for safe cyber physical systems a Medical Case Study
    International Conference on Cyber-Physical Systems, 2013
    Co-Authors: Ayan Banerjee, Sandeep K. S. Gupta
    Abstract:

    Interactions between the computing units and the physical environment in Cyber-Physical Systems (CPSes) are considered to verify safety properties, i.e. ensuring the un-intentional side-effects of cyber-physical interactions are within desired limits. A Linear 1 space dimension Spatio-Temporal Hybrid Automata (L1STHA) is defined to capture the effects of the interactions, in both time and space. Aggregate effects of interactions due to concurrent operations in the computing entities are expressed as a set of interdependent partial differential equations associated with dedicated modes of the L1STHA model. A time and space bound L1STHA reachability analysis algorithm is proposed for safety verification, which provides reachable states of the L1STHA with an arbitrary accuracy e. The runtime of the algorithm depends on the requested accuracy. The usage of the L1STHA modeling and analysis is demonstrated for Medical CPSes such as infusion pumps.

  • ICCPS - Spatio-temporal hybrid automata for safe cyber-physical systems: a Medical Case Study
    Proceedings of the ACM IEEE 4th International Conference on Cyber-Physical Systems - ICCPS '13, 2013
    Co-Authors: Ayan Banerjee, Sandeep K. S. Gupta
    Abstract:

    Interactions between the computing units and the physical environment in Cyber-Physical Systems (CPSes) are considered to verify safety properties, i.e. ensuring the un-intentional side-effects of cyber-physical interactions are within desired limits. A Linear 1 space dimension Spatio-Temporal Hybrid Automata (L1STHA) is defined to capture the effects of the interactions, in both time and space. Aggregate effects of interactions due to concurrent operations in the computing entities are expressed as a set of interdependent partial differential equations associated with dedicated modes of the L1STHA model. A time and space bound L1STHA reachability analysis algorithm is proposed for safety verification, which provides reachable states of the L1STHA with an arbitrary accuracy e. The runtime of the algorithm depends on the requested accuracy. The usage of the L1STHA modeling and analysis is demonstrated for Medical CPSes such as infusion pumps.

Giovanni Russello - One of the best experts on this subject based on the ideXlab platform.

  • A Consent-based Workflow System for Healthcare Systems
    2015
    Co-Authors: Giovanni Russello, Changyu Dong, Naranker Dulay
    Abstract:

    In this paper, we describe a new framework for healthcare systems where patients are able to control the disclosure of their Medical data. In our framework, the patient's consent has a pivotal role in granting or removing access rights to subjects accessing patient's Medical data. Depending on the context in which the access is being executed, different consent policies can be applied. Context is expressed in terms of workflows. The execution of a task in a given workflow carries the necessary information to infer whether the consent can be implicitly retrieved or should be explicitly requested from a patient. However, patients are always able to enforce their own decisions and withdraw consent if necessary. Additionally, the use of workflows enables us to apply the need-to-know principle. Even when the patient's consent is obtained, a subject should access Medical data only if it is required by the actual situation. For example, if the subject is assigned to the execution of a Medical diagnosis workflow requiring access to the patient's Medical record. We also provide a complex Medical Case Study to highlight the design principles behind our framework. Finally, the implementation of the framework is outlined.

  • Consent-Based Workflows for Healthcare Management
    2008 IEEE Workshop on Policies for Distributed Systems and Networks, 2008
    Co-Authors: Giovanni Russello, Changyu Dong, Naranker Dulay
    Abstract:

    In this paper, we describe a new framework for healthcare systems where patients are able to control the disclosure of their Medical data. In our framework, the patient's consent has a pivotal role in granting or removing access rights to subjects accessing patient's Medical data. Depending on the context in which the access is being executed, different consent policies can be applied. Context is expressed in terms of workflows. The execution of a task in a given workflow carries the necessary information to infer whether the consent can be implicitly retrieved or should be explicitly requested from a patient. However, patients are always able to enforce their own decisions and withdraw consent if necessary. Additionally, the use of workflows enables us to apply the need-to-know principle. Even when the patient's consent is obtained, a subject should access Medical data only if it is required by the actual situation. For example, if the subject is assigned to the execution of a Medical diagnosis workflow requiring access to the patient's Medical record. We also provide a complex Medical Case Study to highlight the design principles behind our framework. Finally, the implementation of the framework is outlined.

  • POLICY - Consent-Based Workflows for Healthcare Management
    2008 IEEE Workshop on Policies for Distributed Systems and Networks, 2008
    Co-Authors: Giovanni Russello, Changyu Dong, Naranker Dulay
    Abstract:

    In this paper, we describe a new framework for healthcare systems where patients are able to control the disclosure of their Medical data. In our framework, the patient's consent has a pivotal role in granting or removing access rights to subjects accessing patient's Medical data. Depending on the context in which the access is being executed, different consent policies can be applied. Context is expressed in terms of workflows. The execution of a task in a given workflow carries the necessary information to infer whether the consent can be implicitly retrieved or should be explicitly requested from a patient. However, patients are always able to enforce their own decisions and withdraw consent if necessary. Additionally, the use of workflows enables us to apply the need-to-know principle. Even when the patient's consent is obtained, a subject should access Medical data only if it is required by the actual situation. For example, if the subject is assigned to the execution of a Medical diagnosis workflow requiring access to the patient's Medical record. We also provide a complex Medical Case Study to highlight the design principles behind our framework. Finally, the implementation of the framework is outlined.

  • A Workflow-Based Access Control Framework for e-Health Applications
    22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008), 2008
    Co-Authors: Giovanni Russello, Changyu Dong, Naranker Dulay
    Abstract:

    In this paper, we present a framework where access rights are provided to entities on the basis of the actual task that the entities must fulfill as part of their duties. For capturing the requirements of entities' duties we use the notion of workflow. Our main aim is to provide an access control mechanism that is able to balance the competing goals of flexibility and security. As the main beneficiary of our approach we consider e-Health Applications, where flexibility and security are major requirements. We also provide an implementation of a Medical Case Study to illustrate the framework.

  • AINA Workshops - A Workflow-Based Access Control Framework for e-Health Applications
    22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008), 2008
    Co-Authors: Giovanni Russello, Changyu Dong, Naranker Dulay
    Abstract:

    In this paper, we present a framework where access rights are provided to entities on the basis of the actual task that the entities must fulfill as part of their duties. For capturing the requirements of entities' duties we use the notion of workflow. Our main aim is to provide an access control mechanism that is able to balance the competing goals of flexibility and security. As the main beneficiary of our approach we consider e-Health Applications, where flexibility and security are major requirements. We also provide an implementation of a Medical Case Study to illustrate the framework.

Franco Turini - One of the best experts on this subject based on the ideXlab platform.

  • ICDM Workshops - Time-Annotated Sequences for Medical Data Mining
    Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007), 2007
    Co-Authors: Michele Berlingerio, Francesco Bonchi, Fosca Giannotti, Franco Turini
    Abstract:

    A typical structure of Medical data is a sequence of observations of clinical parameters taken at different time moments. In this kind of contexts, the temporal dimension of data is a fundamental variable that should be taken into account in the mining process and returned as part of the extracted knowledge. Therefore, the classical and well established framework of sequential pattern mining is not enough, because it only focuses on the sequentiality of events, without extracting the typical time elapsing between two particular events. Time-annotated sequences (IAS) is a novel mining paradigm that solves this problem. Recently defined in our laboratory [4] together with an efficient algorithm for extracting them, TAS are sequential patterns where each transition between two events is annotated with a typical transition time that is found frequent in the data. In this paper we report a real-world Medical Case Study, in which the TAS mining paradigm is applied to clinical data regarding a set of patients in the follow-up of a liver transplantation. The aim of the data analysis is that of assessing the effectiveness of the extracorporeal photopheresis (ECP) as a therapy to prevent rejection in solid organ transplantation. We believe that this Case Study does not only show the interestingness of extracting TAS patterns in this particular context but, more ambitiously, it suggests a general methodology for clinical data mining, whenever the time dimension is an important variable of the problem under investigation.

  • Time-Annotated Sequences for Medical Data Mining
    Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007), 2007
    Co-Authors: Michele Berlingerio, Francesco Bonchi, Fosca Giannotti, Franco Turini
    Abstract:

    A typical structure of Medical data is a sequence of observations of clinical parameters taken at different time moments. In this kind of contexts, the temporal dimension of data is a fundamental variable that should be taken into account in the mining process and returned as part of the extracted knowledge. Therefore, the classical and well established framework of sequential pattern mining is not enough, because it only focuses on the sequentiality of events, without extracting the typical time elapsing between two particular events. Time-annotated sequences (IAS) is a novel mining paradigm that solves this problem. Recently defined in our laboratory [4] together with an efficient algorithm for extracting them, TAS are sequential patterns where each transition between two events is annotated with a typical transition time that is found frequent in the data. In this paper we report a real-world Medical Case Study, in which the TAS mining paradigm is applied to clinical data regarding a set of patients in the follow-up of a liver transplantation. The aim of the data analysis is that of assessing the effectiveness of the extracorporeal photopheresis (ECP) as a therapy to prevent rejection in solid organ transplantation. We believe that this Case Study does not only show the interestingness of extracting TAS patterns in this particular context but, more ambitiously, it suggests a general methodology for clinical data mining, whenever the time dimension is an important variable of the problem under investigation.

  • Mining Clinical Data with a Temporal Dimension: A Case Study
    2007 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2007), 2007
    Co-Authors: Michele Berlingerio, Francesco Bonchi, Fosca Giannotti, Franco Turini
    Abstract:

    Clinical databases store large amounts of information about patients and their Medical conditions. Data mining techniques can extract relationships and patterns holding in this wealth of data, and thus be helpful in understanding the progression of diseases and the efficacy of the associated therapies. A typical structure of Medical data is a sequence of observations of clinical parameters taken at different time moments. In this kind of contexts, the temporal dimension of data is a fundamental variable that should be taken in account in the mining process and returned as part of the extracted knowledge. Therefore, the classical and well established framework of sequential pattern mining is not enough, because it only focuses on the sequentiality of events, without extracting the typical time elapsing between two particular events. Time-annotated sequences (IAS), is a novel mining paradigm that solves this problem. Recently defined in our laboratory together with an efficient algorithm for extracting them, IAS are sequential patterns where each transition between two events is annotated with a typical transition time that is found frequent in the data. In this paper we report a real-world Medical Case Study, in which the IAS mining paradigm is applied to clinical data regarding a set of patients in the follow-up of a liver transplantation. The aim of the data analysis is that of assessing the effectiveness of the extracorporeal photopheresis (ECP) as a therapy to prevent rejection in solid organ transplantation. For each patient, a set of biochemical variables is recorded at different time moments after the transplantation. The IAS patterns extracted show the values of interleukins and other clinical parameters at specific dates, from which it is possible for the physician to assess the effectiveness of the ECP therapy. We believe that this Case Study does not only show the interestingness of extracting IAS patterns in this particular context but, more ambitiously, it suggests a general methodology for clinical data mining, whenever the time dimension is an important variable of the problem in analysis.

Pasi Liljeberg - One of the best experts on this subject based on the ideXlab platform.

  • exploiting smart e health gateways at the edge of healthcare internet of things
    Future Generation Computer Systems, 2018
    Co-Authors: Amir-mohammad Rahmani, Mingzhe Jiang, Arman Anzanpour, Behailu Negash, Iman Azimi, Pasi Liljeberg
    Abstract:

    Current developments in ICTs such as in Internet-of-Things (IoT) and CyberPhysical Systems (CPS) allow us to develop healthcare solutions with more intelligent and prediction capabilities both for daily life (home/office) and in-hospitals. In most of IoT-based healthcare systems, especially at smart homes or hospitals, a bridging point (i.e.,gateway) is needed between sensor infrastructure network and the Internet. The gateway at the edge of the network often just performs basic functions such as translating between the protocols used in the Internet and sensor networks. These gateways have beneficial knowledge and constructive control over both the sensor network and the data to be transmitted through the Internet. In this paper, we exploit the strategic position of such gateways at the edge of the network to offer several higher-level services such as local storage, real-time local data processing, embedded data mining, etc., presenting thus a Smart e-Health Gateway. We then propose to exploit the concept of Fog Computing in Healthcare IoT systems by forming a Geo-distributed intermediary layer of intelligence between sensor nodes and Cloud. By taking responsibility for handling some burdens of the sensor network and a remote healthcare center, our Fog-assisted system architecture can cope with many challenges in ubiquitous healthcare systems such as mobility, energy efficiency, scalability, and reliability issues. A successful implementation of Smart e-Health Gateways can enable massive deployment of ubiquitous health monitoring systems especially in clinical environments. We also present a prototype of a Smart e-Health Gateway called UT-GATE where some of the discussed higher-level features have been implemented. We also implement an IoT-based Early Warning Score (EWS) health monitoring to practically show the efficiency and relevance of our system on addressing a Medical Case Study. Our proof-of-concept design demonstrates an IoT-based health monitoring system with enhanced overall system intelligence, energy efficiency, mobility, performance, interoperability, security, and reliability.

  • Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach
    Future Generation Computer Systems, 2016
    Co-Authors: Amir-mohammad Rahmani, Mingzhe Jiang, Arman Anzanpour, Behailu Negash, Tuan Nguyen Gia, Amir Masoud Rahmani, Iman Azimi, Pasi Liljeberg
    Abstract:

    Current developments in ICTs such as in Internet-of-Things (IoT) and Cyber-Physical Systems (CPS) allow us to develop healthcare solutions with more intelligent and prediction capabilities both for daily life (home/office) and in-hospitals. In most of IoT-based healthcare systems, especially at smart homes or hospitals, a bridging point (i.e., gateway) is needed between sensor infrastructure network and the Internet. The gateway at the edge of the network often just performs basic functions such as translating between the protocols used in the Internet and sensor networks. These gateways have beneficial knowledge and constructive control over both the sensor network and the data to be transmitted through the Internet. In this paper, we exploit the strategic position of such gateways at the edge of the network to offer several higher-level services such as local storage, real-time local data processing, embedded data mining, etc., presenting thus a Smart e-Health Gateway. We then propose to exploit the concept of Fog Computing in Healthcare IoT systems by forming a Geo-distributed intermediary layer of intelligence between sensor nodes and Cloud. By taking responsibility for handling some burdens of the sensor network and a remote healthcare center, our Fog-assisted system architecture can cope with many challenges in ubiquitous healthcare systems such as mobility, energy efficiency, scalability, and reliability issues. A successful implementation of Smart e-Health Gateways can enable massive deployment of ubiquitous health monitoring systems especially in clinical environments. We also present a prototype of a Smart e-Health Gateway called UT-GATE where some of the discussed higher-level features have been implemented. We also implement an IoT-based Early Warning Score (EWS) health monitoring to practically show the efficiency and relevance of our system on addressing a Medical Case Study. Our proof-of-concept design demonstrates an IoT-based health monitoring system with enhanced overall system intelligence, energy efficiency, mobility, performance, interoperability, security, and reliability.