ORCID Profile
0000-0002-4415-5771
Current Organisation
Federation University Australia
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Publisher: Elsevier BV
Date: 2014
Publisher: ACM
Date: 06-06-2005
Publisher: Springer Berlin Heidelberg
Date: 1998
Publisher: ACM
Date: 04-02-2020
Publisher: ACM
Date: 08-06-2019
Publisher: Hindawi Limited
Date: 22-11-2022
DOI: 10.1155/2022/1578791
Abstract: Over the last few years, business simulation games (BSGs) in higher education have attracted attention. BSGs tend to actively engage students with course material, promoting higher engagement and motivation and enabling learning outcomes. Increasingly, researchers are trying to explore the full potential of these games with an upsurge of research in the BSG field in recent years. There is a need to understand the current state of research and future research opportunities however, there is a lack of recent systematic literature reviews in BSG literature. This study addresses this gap by systematically compiling online empirical research from January 2015 to April 2022. We followed PRISMA guidelines to identify fifty-seven (57) papers reporting empirical evidence of the effectiveness of BSGs in teaching and learning. Findings showed that BSGs improve learning outcomes such as knowledge acquisition, cognitive and interactive skills, and behaviour. The review also summarises different issues concerning the integration of BSGs into the curriculum, learning theories used in the selected studies, and assessment methods used to evaluate student achievement in learning outcomes. The findings of this review summarise the current research activities and indicate existing deficiencies and potential research directions that can be used as the basis for future research into the use of BSGs in higher education.
Publisher: IGI Global
Date: 2006
DOI: 10.4018/978-1-59140-702-7.CH016
Abstract: This chapter introduces an approach, ConSULT (Consensus based on a Shared Understanding of a Leading Topic), to enhance group decision-making processes within organizations. ConSULT provides a computer-mediated framework to allow argumentation, collection and evaluation of discussion and group decision-making. This approach allows for the articulation of all reasoning for and against propositions in a deliberative process that leads to cooperative decision-making. The chapter argues that this approach can enhance group decision-making and can be used in conjunction with any computational intelligence assistance to further enhance its outcome. The approach is particularly applicable in an asynchronous and anonymous environment.
Publisher: Springer Science and Business Media LLC
Date: 08-05-2017
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Elsevier BV
Date: 10-2013
DOI: 10.1016/J.COMPBIOMED.2013.07.002
Abstract: Cardiovascular autonomic neuropathy (CAN) is a serious and well known complication of diabetes. Previous articles circumvented the problem of missing values in CAN data by deleting all records and fields with missing values and applying classifiers trained on different sets of features that were complete. Most of them also added alternative features to compensate for the deleted ones. Here we introduce and investigate a new method for classifying CAN data with missing values. In contrast to all previous papers, our new method does not delete attributes with missing values, does not use classifiers, and does not add features. Instead it is based on regression and meta-regression combined with the Ewing formula for identifying the classes of CAN. This is the first article using the Ewing formula and regression to classify CAN. We carried out extensive experiments to determine the best combination of regression and meta-regression techniques for classifying CAN data with missing values. The best outcomes have been obtained by the additive regression meta-learner based on M5Rules and combined with the Ewing formula. It has achieved the best accuracy of 99.78% for two classes of CAN, and 98.98% for three classes of CAN. These outcomes are substantially better than previous results obtained in the literature by deleting all missing attributes and applying traditional classifiers to different sets of features without regression. Another advantage of our method is that it does not require practitioners to perform more tests collecting additional alternative features.
Publisher: IEEE
Date: 03-2019
Publisher: Elsevier BV
Date: 03-2020
Publisher: Springer Netherlands
Date: 2005
Publisher: ACM
Date: 05-2001
Publisher: Springer Netherlands
Date: 2005
Publisher: SAGE Publications
Date: 08-07-2016
Abstract: The purpose of this research was to conduct a cost-analysis, from a public healthcare perspective, comparing the cost and benefits of face-to-face patient examination assessments conducted by a dentist at a residential aged care facility (RACF) situated in rural areas of the Australian state of Victoria, with two teledentistry approaches utilizing virtual oral examination. The costs associated with implementing and operating the teledentistry approach were identified and measured using 2014 prices in Australian dollars. Costs were measured as direct intervention costs and programme costs. A population of 100 RACF residents was used as a basis to estimate the cost of oral examination and treatment plan development for the traditional face-to-face model vs. two teledentistry models: an asynchronous review and treatment plan preparation and real-time communication with a remotely located oral health professional. It was estimated that if 100 residents received an asynchronous oral health assessment and treatment plan, the net cost from a healthcare perspective would be AU$32.35 (AU$27.19–AU$38.49) per resident. The total cost of the conventional face-to-face examinations by a dentist would be AU$36.59 ($30.67–AU$42.98) per resident using realistic assumptions. Meanwhile, the total cost of real-time remote oral examination would be AU$41.28 (AU$34.30–AU$48.87) per resident. Teledental asynchronous patient assessments were the lowest cost service model. Access to oral health professionals is generally low in RACFs however, the real-time consultation could potentially achieve better outcomes due to two-way communication between the nurse and a remote oral health professional via health promotion/disease prevention delivered in conjunction with the oral examination.
Publisher: Springer Netherlands
Date: 2005
Publisher: IEEE
Date: 12-2016
Publisher: Springer Netherlands
Date: 2005
Publisher: Springer Netherlands
Date: 2005
Publisher: Springer Netherlands
Date: 2005
Publisher: IGI Global
Date: 2010
DOI: 10.4018/978-1-60960-091-4.CH013
Abstract: In software engineering, the re-use concept is a design principle that improves efficiency, quality and maintainability by ensuring that software artifacts are developed once and re-used many times. In an analogous way, a group‘s reasoning can be imagined to be re-used by that or another group to enhance efficiency, transparency and consistency in decision-making. However, the re-use of reasoning is difficult to achieve because group reasoning cannot easily be captured and the way in which a group reasoning artifact is subsequently used is not obvious. This chapter explores the case for the re-use of community reasoning and concludes that in iduals can benefit from a representation of a previous group‘s coalesced reasoning if the reasoning to be modeled and the scheme to represent the reasoning have been selected to suit the task. The authors contend that specifying the future community likely to re-use the reasoning, called the intended audience, informs a decision regarding whether an exercise aimed at coalescing a group‘s reasoning is best performed verbally, in writing or with the use of more structured schemes such as Argument visualization.
Publisher: Springer Netherlands
Date: 2005
Publisher: Springer Science and Business Media LLC
Date: 03-01-2021
Publisher: Springer Netherlands
Date: 2005
Publisher: Informa UK Limited
Date: 12-2008
Publisher: IGI Global
Date: 2010
DOI: 10.4018/978-1-60960-091-4.CH006
Abstract: This chapter describes some of the current approaches to deliberative democracy and then considers them from the perspective of a reasoning community framework. This approach highlights important tasks, processes and structures that can be used to enhance the processes of groups engaging in deliberative democracy approaches. In particular it focuses attention on the potential for technologies to support groups in achieving broad agreed structured reasoning bases that capture the scope of an issue from multiple perspectives.
Publisher: ACM
Date: 02-2021
Publisher: ACM
Date: 02-2021
Publisher: IEEE
Date: 06-2012
Publisher: IEEE
Date: 10-2014
Publisher: IEEE
Date: 12-2008
Publisher: ACM Press
Date: 1997
Publisher: ACM
Date: 29-01-2019
Publisher: JMIR Publications Inc.
Date: 16-12-2019
DOI: 10.2196/14684
Abstract: With the growing use of social media in health care settings, there is a need to measure outcomes resulting from its use to ensure continuous performance improvement. Despite the need for measurement, a unified approach for measuring the value of social media used in health care remains elusive. This study aimed to elucidate how the value of social media in health care settings can be ascertained and to taxonomically identify steps and techniques in social media measurement from a review of relevant literature. A total of 65 relevant articles drawn from 341 articles on the subject of measuring social media in health care settings were qualitatively analyzed and synthesized. The articles were selected from the literature from erse disciplines including business, information systems, medical informatics, and medicine. The review of the literature showed different levels and focus of analysis when measuring the value of social media in health care settings. It equally showed that there are various metrics for measurement, levels of measurement, approaches to measurement, and scales of measurement. Each may be relevant, depending on the use case of social media in health care. A comprehensive yardstick is required to simplify the measurement of outcomes resulting from the use of social media in health care. At the moment, there is neither a consensus on what indicators to measure nor on how to measure them. We hope that this review is used as a starting point to create a comprehensive measurement criterion for social media used in health care.
Publisher: Informa UK Limited
Date: 05-2002
Publisher: Springer Science and Business Media LLC
Date: 1995
DOI: 10.1007/BF00871852
Publisher: JMIR Publications Inc.
Date: 18-08-2019
Abstract: ocial media is increasingly used by healthcare providers. However, despite the growing adoption of the application in healthcare settings, the various contexts of use and the value proposition in each context are not well understood. his study aimed to explore the uses of social media in healthcare settings and the value proposition in each context of use, using a qualitative methodology. The affordances of social media and how healthcare providers appropriate social media for health-related activities are also explored from a Uses and Gratification Theory perspective. his study is an exploratory qualitative research study. Australian healthcare providers that use social media were contacted to participate in the study. Data was collected through semi-structured interviews and the transcripts were analysed using thematic analysis, to identify common themes expressed across participants. ine contexts of use of healthcare social media emerged: professional networking, harnessing patient feedback, public health promotion, professional education, patient education, organizational promotion, crowdsourcing, research, and patient collaboration. Results indicates that healthcare providers are not passive users of information systems, rather, they make conscious decisions regarding if, when and how to use social media. Thus, healthcare providers use social media because they believe that it will help them realize the gratification or value they seek. his study conclude that the value of social media in healthcare lie in its potential to support various activities in healthcare settings. However, its value proposition varies depending on context of use.
Publisher: IEEE
Date: 04-2013
Publisher: Computing in Cardiology
Date: 14-09-2017
Publisher: Springer Berlin Heidelberg
Date: 1999
Publisher: IEEE
Date: 12-2018
Publisher: IEEE
Date: 10-2019
Publisher: Elsevier BV
Date: 04-2017
Publisher: IEEE
Date: 10-2021
Publisher: ACM
Date: 04-02-2020
Publisher: IEEE
Date: 12-2010
Publisher: Springer Singapore
Date: 09-08-2019
Publisher: SAGE Publications
Date: 2019
Abstract: The aim of the current study is to generate waist circumference to height ratio cut-off values for obesity categories from a model of the relationship between body mass index and waist circumference to height ratio. We compare the waist circumference to height ratio discovered in this way with cut-off values currently prevalent in practice that were originally derived using pragmatic criteria. Personalized data including age, gender, height, weight, waist circumference and presence of diabetes, hypertension and cardiovascular disease for 847 participants over eight years were assembled from participants attending a rural Australian health review clinic (DiabHealth). Obesity was classified based on the conventional body mass index measure (weight/height 2 ) and compared to the waist circumference to height ratio. Correlations between the measures were evaluated on the screening data, and independently on data from the National Health and Nutrition Examination Survey that included age categories. This article recommends waist circumference to height ratio cut-off values based on an Australian rural s le and verified using the National Health and Nutrition Examination Survey database that facilitates the classification of obesity in clinical practice. Gender independent cut-off values are provided for waist circumference to height ratio that identify healthy (waist circumference to height ratio ≥0.45), overweight (0.53) and the three obese (0.60, 0.68, 0.75) categories verified on the National Health and Nutrition Examination Survey dataset. A strong linearity between the waist circumference to height ratio and the body mass index measure is demonstrated. The recommended waist circumference to height ratio cut-off values provided a useful index for assessing stages of obesity and risk of chronic disease for improved healthcare in clinical practice.
Publisher: IGI Global
Date: 2012
DOI: 10.4018/978-1-4666-1833-6.CH006
Abstract: The central theme of this chapter is that the application of machine learning to data in the legal domain involves considerations that derive from jurisprudential assumptions about the nature of legal reasoning. Jurisprudence provides a unique resource for machine learning in that, for over one hundred years, significant thinkers have advanced concepts including open texture and discretion. These concepts inform and guide applications of machine learning to law.
Publisher: ACM
Date: 14-02-2022
Publisher: Springer Science and Business Media LLC
Date: 18-06-2013
Publisher: IEEE
Date: 10-2016
Publisher: IGI Global
Date: 10-2013
Abstract: Cardiac complications of diabetes require continuous monitoring since they may lead to increased morbidity or sudden death of patients. In order to monitor clinical complications of diabetes using wearable sensors, a small set of features have to be identified and effective algorithms for their processing need to be investigated. This article focuses on detecting and monitoring cardiac autonomic neuropathy (CAN) in diabetes patients. The authors investigate and compare the effectiveness of classifiers based on the following decision trees: ADTree, J48, NBTree, RandomTree, REPTree, and SimpleCart. The authors perform a thorough study comparing these decision trees as well as several decision tree ensembles created by applying the following ensemble methods: AdaBoost, Bagging, Dagging, Decorate, Grading, MultiBoost, Stacking, and two multi-level combinations of AdaBoost and MultiBoost with Bagging for the processing of data from diabetes patients for pervasive health monitoring of CAN. This paper concentrates on the particular task of applying decision tree ensembles for the detection and monitoring of cardiac autonomic neuropathy using these features. Experimental outcomes presented here show that the authors' application of the decision tree ensembles for the detection and monitoring of CAN in diabetes patients achieved better performance parameters compared with the results obtained previously in the literature.
Publisher: IEEE
Date: 24-11-2022
Publisher: Emerald
Date: 15-12-2020
DOI: 10.1108/JICES-06-2020-0071
Abstract: This paper aims to use the writings of Mikhail Bakhtin to reveal new insights into the role and impact of social media in health-care settings. With the help of Bakhtin’s constructs of dialogism, polyphony, heteroglossia and carnival, the power and influences of the social media phenomenon in health-care settings, are explored. It is apparent from the in-depth analysis conducted that there is a delicate balance between the need to increase dialogue and the need to safeguard public health, in the use of social media for health-related communication. Bakhtin‘s constructs elucidate this delicate balance and highlight the need for health-care providers that use social media to find the right balance between these competing communicational priorities. This paper advances a nascent theoretical approach to social media research. By applying Bakhtinian ideas to consumer health informatics, this paper has the potential to open a new approach to theorizing the role of social software in health-care settings. Stakeholders in digital health will find this paper useful, as it opens up dialogue to further discuss the role of social media in health care.
Publisher: Springer Berlin Heidelberg
Date: 1999
Publisher: IEEE
Date: 04-2017
Publisher: IEEE
Date: 02-2014
Publisher: Cambridge University Press (CUP)
Date: 12-2001
DOI: 10.1017/S0269888901000248
Abstract: Argumentation concepts have been applied to numerous knowledge engineering endeavours in recent years. For ex le, a variety of logics have been developed to represent argumentation in the context of a dialectical situation such as a dialogue. In contrast to the dialectical approach, argumentation has also been used to structure knowledge. This can be seen as a non-dialectical approach. The Toulmin argument structure has often been used to structure knowledge non-dialectically yet most studies that apply the Toulmin structure do not use the original structure but vary one or more components. Variations to the Toulmin structure can be understood as different ways to integrate a dialectical perspective with a non-dialectical one. Drawing the dialectical/non-dialectical distinction enables the specification of a framework called the generic actual argument model that is expressly non-dialectical. The framework enables the development of knowledge-based systems that integrate a variety of inference procedures, combine information retrieval with reasoning and facilitate automated document drafting. Furthermore, the non-dialectical framework provides the foundation for simple dialectical models. Systems based on our approach have been developed in family law, refugee law, determining eligibility for government legal aid, copyright law and e-tourism.
Publisher: IEEE
Date: 09-2010
DOI: 10.1109/NSS.2010.7
Publisher: Emerald
Date: 04-07-2008
DOI: 10.1108/09699980810886847
Abstract: The purpose of this paper is to describe an innovative information and decision support tool (ToolSHeD™) developed to help construction designers to integrate the management of OHS risk into the design process. The underlying structure of the prototype web‐based system and the process of knowledge acquisition and modelling are described. The ToolSHeD™ research and development project involved the capture of expert reasoning regarding design impacts upon occupational health and safety (OHS) risk. This knowledge was structured using an innovative method well‐suited to modelling knowledge in the context of uncertainty and discretionary decision‐making. Ex le “argument trees” are presented, representing the reasoning used by a panel of experts to assess the risk of falling from height during roof maintenance work. The advantage of using this method for modelling OHS knowledge, compared to the use of simplistic rules, is discussed The ToolSHeD™ prototype development and testing reveals that argument trees can represent design safety risk knowledge effectively. The translation of argument trees into a web‐based decision support tool is described and the potential impact of this tool in providing construction designers (architects and engineers) with easy and inexpensive access to expert OHS knowledge is discussed. The paper describes a new computer application, currently undergoing testing in the Australian building and construction industry. Its originality lies in the fact that ToolSHeD™ deploys argument trees to represent expert OHS reasoning, overcoming inherent limitations in rule‐based expert systems.
Publisher: ACM
Date: 14-05-2021
Publisher: ACM
Date: 14-02-2022
Publisher: ACM
Date: 29-01-2019
Publisher: Elsevier BV
Date: 06-2022
Publisher: Oxford University Press (OUP)
Date: 06-1998
Publisher: Elsevier BV
Date: 06-2021
Publisher: Springer Science and Business Media LLC
Date: 16-12-2006
Publisher: IGI Global
Date: 2016
DOI: 10.4018/978-1-5225-0920-2.CH036
Abstract: Recently, we are witnessing an exponential growth in remote monitoring and mobile applications for healthcare. These solutions are all designed to ultimately enable the consumer to enjoy better healthcare delivery and /or wellness. In order to understand this growing area, we believe it is necessary to develop a framework to analyse and evaluate these solutions. The purpose of this chapter then is to offer a suitable taxonomy to systematically analyse and evaluate the existing solutions based on number of dimensions including technological, clinical, social, and economic.
Publisher: IEEE
Date: 04-2018
Publisher: Springer Science and Business Media LLC
Date: 17-08-2018
Publisher: Springer Science and Business Media LLC
Date: 23-04-2009
Publisher: ACM
Date: 19-05-2017
Publisher: Elsevier BV
Date: 07-2013
DOI: 10.1016/J.ARTMED.2013.04.007
Abstract: This article addresses the problem of determining optimal sequences of tests for the clinical assessment of cardiac autonomic neuropathy (CAN). We investigate the accuracy of using only one of the recommended Ewing tests to classify CAN and the additional accuracy obtained by adding the remaining tests of the Ewing battery. This is important as not all five Ewing tests can always be applied in each situation in practice. We used new and unique database of the diabetes screening research initiative project, which is more than ten times larger than the data set used by Ewing in his original investigation of CAN. We utilized decision trees and the optimal decision path finder (ODPF) procedure for identifying optimal sequences of tests. We present experimental results on the accuracy of using each one of the recommended Ewing tests to classify CAN and the additional accuracy that can be achieved by adding the remaining tests of the Ewing battery. We found the best sequences of tests for cost-function equal to the number of tests. The accuracies achieved by the initial segments of the optimal sequences for 2, 3 and 4 categories of CAN are 80.80, 91.33, 93.97 and 94.14, and respectively, 79.86, 89.29, 91.16 and 91.76, and 78.90, 86.21, 88.15 and 88.93. They show significant improvement compared to the sequence considered previously in the literature and the mathematical expectations of the accuracies of a random sequence of tests. The complete outcomes obtained for all subsets of the Ewing features are required for determining optimal sequences of tests for any cost-function with the use of the ODPF procedure. We have also found two most significant additional features that can increase the accuracy when some of the Ewing attributes cannot be obtained. The outcomes obtained can be used to determine the optimal sequences of tests for each in idual cost-function by following the ODPF procedure. The results show that the best single Ewing test for diagnosing CAN is the deep breathing heart rate variation test. Optimal sequences found for the cost-function equal to the number of tests guarantee that the best accuracy is achieved after any number of tests and provide an improvement in comparison with the previous ordering of tests or a random sequence.
Publisher: IEEE
Date: 1999
Publisher: MDPI AG
Date: 16-12-2019
DOI: 10.3390/ELECTRONICS8121552
Abstract: The Internet of Things (IoT) has facilitated services without human intervention for a wide range of applications, including underwater monitoring, where sensors are located at various depths, and data must be transmitted to surface base stations for storage and processing. Ensuring that data transmitted across hierarchical sensor networks are kept secure and private without high computational cost remains a challenge. In this paper, we propose a multilevel sensor monitoring architecture. Our proposal includes a layer-based architecture consisting of Fog and Cloud elements to process and store and process the Internet of Underwater Things (IoUT) data securely with customized Blockchain technology. The secure routing of IoUT data through the hierarchical topology ensures the legitimacy of data sources. A security and performance analysis was performed to show that the architecture can collect data from IoUT devices in the monitoring region efficiently and securely.
Publisher: Springer Science and Business Media LLC
Date: 05-06-2015
Publisher: Informa UK Limited
Date: 10-05-2016
Publisher: Informa UK Limited
Date: 10-06-2016
Publisher: IGI Global
Date: 2021
DOI: 10.4018/978-1-7998-4963-6.CH001
Abstract: Intelligent analytics is an emerging paradigm in the age of big data, analytics, and artificial intelligence (AI). This chapter explores the nature of intelligent analytics. More specifically, this chapter identifies the foundations, cores, and applications of intelligent big data analytics based on the investigation into the state-of-the-art scholars' publications and market analysis of advanced analytics. Then it presents a workflow-based approach to big data analytics and technological foundations for intelligent big data analytics through examining intelligent big data analytics as an integration of AI and big data analytics. The chapter also presents a novel approach to extend intelligent big data analytics to intelligent analytics. The proposed approach in this chapter might facilitate research and development of intelligent analytics, big data analytics, business analytics, business intelligence, AI, and data science.
Publisher: Kluwer Academic Publishers
Date: 2006
Publisher: IEEE Comput. Soc. Press
Date: 1995
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: IGI Global
Date: 2021
DOI: 10.4018/978-1-7998-4963-6.CH003
Abstract: This chapter addresses whether AI can understand me. A framework for regulating AI systems that draws on Strawson's moral philosophy and concepts drawn from jurisprudence and theories on regulation is used. This chapter proposes that, as AI algorithms increasingly draw inferences following repeated exposure to big datasets, they have become more sophisticated and rival human reasoning. Their regulation requires that AI systems have agency and are subject to the rulings of courts. Humans sponsor the AI systems for registration with regulatory agencies. This enables judges to make moral culpability decisions by taking the AI system's explanation into account along with the full social context of the misdemeanor. The proposed approach might facilitate the research and development of intelligent analytics, intelligent big data analytics, multiagent systems, artificial intelligence, and data science.
Publisher: IGI Global
Date: 2022
DOI: 10.4018/978-1-7998-9016-4.CH005
Abstract: Frameworks for the regulation of artificial intelligence (AI) systems are emerging some are based on regulation theories others are more technologically focused. Regulation of AI systems is likely to emerge in an ad-hoc, unstructured, and uncoordinated fashion that renders high level frameworks philosophically interesting but of limited benefit in practice. In this paper, the task of arriving at a collection of interventions that regulate an AI system is taken to be a process-oriented problem. It presents a process-oriented framework for the design of regulating systems by deliberating groups. It also discusses regulations of AI systems and responsibility, mechanisms and institutions, key elements for regulating AI systems. The proposed approach might facilitate research and development of responsible AI, explainable AI, and ethical AI for an ethical and inclusive digitized society. It also has implications for the development of e-business, e-services, and e-society.
Publisher: Informa UK Limited
Date: 03-2001
Publisher: ACM
Date: 29-01-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: IEEE Comput. Soc
Date: 2000
Publisher: ACM Press
Date: 1995
Publisher: Informa UK Limited
Date: 26-07-2019
Publisher: IGI Global
Date: 2020
DOI: 10.4018/978-1-5225-9863-3.CH040
Abstract: Recently, we are witnessing an exponential growth in remote monitoring and mobile applications for healthcare. These solutions are all designed to ultimately enable the consumer to enjoy better healthcare delivery and /or wellness. In order to understand this growing area, we believe it is necessary to develop a framework to analyse and evaluate these solutions. The purpose of this chapter then is to offer a suitable taxonomy to systematically analyse and evaluate the existing solutions based on number of dimensions including technological, clinical, social, and economic.
Publisher: ACM
Date: 14-06-1999
Publisher: ACM
Date: 30-01-2023
Publisher: ACM
Date: 30-01-2023
Publisher: ACM Press
Date: 2003
Publisher: IEEE
Date: 09-2012
DOI: 10.1109/NBIS.2012.20
Publisher: SAGE Publications
Date: 24-09-2020
Abstract: Health-related data is stored in a number of repositories that are managed and controlled by different entities. For instance, Electronic Health Records are usually administered by governments. Electronic Medical Records are typically controlled by health care providers, whereas Personal Health Records are managed directly by patients. Recently, Blockchain-based health record systems largely regulated by technology have emerged as another type of repository. Repositories for storing health data differ from one another based on cost, level of security and quality of performance. Not only has the type of repositories increased in recent years, but the quantum of health data to be stored has increased. For instance, the advent of wearable sensors that capture physiological signs has resulted in an exponential growth in digital health data. The increase in the types of repository and amount of data has driven a need for intelligent processes to select appropriate repositories as data is collected. However, the storage allocation decision is complex and nuanced. The challenges are exacerbated when health data are continuously streamed, as is the case with wearable sensors. Although patients are not always solely responsible for determining which repository should be used, they typically have some input into this decision. Patients can be expected to have idiosyncratic preferences regarding storage decisions depending on their unique contexts. In this paper, we propose a predictive model for the storage of health data that can meet patient needs and make storage decisions rapidly, in real-time, even with data streaming from wearable sensors. The model is built with a machine learning classifier that learns the mapping between characteristics of health data and features of storage repositories from a training set generated synthetically from correlations evident from small s les of experts. Results from the evaluation demonstrate the viability of the machine learning technique used.
Publisher: IEEE
Date: 09-2020
Publisher: IEEE
Date: 08-2017
Publisher: ACM Press
Date: 1997
Publisher: IEEE
Date: 12-2014
Publisher: IEEE
Date: 10-2012
Publisher: Elsevier BV
Date: 2006
Publisher: Informa UK Limited
Date: 05-2002
Publisher: IGI Global
Date: 2022
DOI: 10.4018/978-1-6684-3662-2.CH050
Abstract: Remote patient monitoring involves the collection of data from wearable sensors that typically requires analysis in real time. The real-time analysis of data streaming continuously to a server challenges data mining algorithms that have mostly been developed for static data residing in central repositories. Remote patient monitoring also generates huge data sets that present storage and management problems. Although virtual records of every health event throughout an in idual's lifespan known as the electronic health record are rapidly emerging, few electronic records accommodate data from continuous remote patient monitoring. These factors combine to make data analytics with continuous patient data very challenging. In this chapter, benefits for data analytics inherent in the use of standards for clinical concepts for remote patient monitoring is presented. The openEHR standard that describes the way in which concepts are used in clinical practice is well suited to be adopted as the standard required to record meta-data about remote monitoring. The claim is advanced that this is likely to facilitate meaningful real time analyses with big remote patient monitoring data. The point is made by drawing on a case study involving the transmission of patient vital sign data collected from wearable sensors in an Indian hospital.
Publisher: IEEE
Date: 20-03-2021
Publisher: IEEE
Date: 11-2019
Publisher: Auerbach Publications
Date: 12-01-2023
Publisher: Elsevier BV
Date: 08-2016
DOI: 10.1016/J.COMPBIOMED.2016.05.005
Abstract: Glycated haemoglobin (HbA1c) is being more commonly used as an alternative test for the identification of type 2 diabetes mellitus (T2DM) or to add to fasting blood glucose level and oral glucose tolerance test results, because it is easily obtained using point-of-care technology and represents long-term blood sugar levels. HbA1c cut-off values of 6.5% or above have been recommended for clinical use based on the presence of diabetic comorbidities from population studies. However, outcomes of large trials with a HbA1c of 6.5% as a cut-off have been inconsistent for a diagnosis of T2DM. This suggests that a HbA1c cut-off of 6.5% as a single marker may not be sensitive enough or be too simple and miss in iduals at risk or with already overt, undiagnosed diabetes. In this study, data mining algorithms have been applied on a large clinical dataset to identify an optimal cut-off value for HbA1c and to identify whether additional biomarkers can be used together with HbA1c to enhance diagnostic accuracy of T2DM. T2DM classification accuracy increased if 8-hydroxy-2-deoxyguanosine (8-OhdG), an oxidative stress marker, was included in the algorithm from 78.71% for HbA1c at 6.5% to 86.64%. A similar result was obtained when interleukin-6 (IL-6) was included (accuracy=85.63%) but with a lower optimal HbA1c range between 5.73 and 6.22%. The application of data analytics to medical records from the Diabetes Screening programme demonstrates that data analytics, combined with large clinical datasets can be used to identify clinically appropriate cut-off values and identify novel biomarkers that when included improve the accuracy of T2DM diagnosis even when HbA1c levels are below or equal to the current cut-off of 6.5%.
Publisher: Springer International Publishing
Date: 22-08-2014
Publisher: SPIE
Date: 26-05-1999
DOI: 10.1117/12.349424
Publisher: IGI Global
Date: 2011
Publisher: Springer Nature Singapore
Date: 2022
Publisher: ACM
Date: 29-01-2018
Publisher: Emerald
Date: 19-02-2018
DOI: 10.1108/ECAM-07-2016-0174
Abstract: The purpose of this paper is to examine the potential to use infographics to capture, represent and communicate important information to construction designers, such that it improves their ability to understand the implications of design choices for construction workers’ health and safety. Drawing on information obtained through a photographic Q-sort, supplemented with a literature review, health and safety information related to the design of a façade was collected from subject matter experts. This information was used to develop infographics representing the subject matter knowledge. A facilitated workshop was then held with 20 design professionals to engage them in a hazard identification process using a case study scenario. The designers were provided with the infographics and asked to comment upon how the infographics changed their assessments of the health and safety risks inherent in the case study building design. A sub-set of participants was interviewed to explore their perceptions of the impact and usefulness of the inforgraphics. Infographics were developed at different levels of detail, representing potential health and safety issues associated with the site location and surroundings, the construction site environment and the detailed façade design. Workshop participants identified a number of potential health and safety issues associated with the case study scenario. However, this number increased substantially once they had viewed the infographic. Further, the health and safety issues identified when participants had access to the infographic were more likely to be less visible issues, relating to ergonomic hazards, procurement or the organisation and sequencing of work. The workshop participants who were interviewed described how the infographics enabled them to make a more global assessment of the health and safety implications of the case study building design because it helped them to understand the design in the physical construction site context. Participants also favoured the visual nature of the infographics and suggested that this format may be particularly useful to communicate important health and safety information to novice designers with limited on-site experience. The infographics developed in this research were relatively simple two-dimensional representations produced and presented in hard copy format. It is possible that more sophisticated forms of infographic could have produced different results. Thus, it is important that future research develops different types of infographics and rigorously evaluates their effectiveness in developing designers’ health and safety-related knowledge and improving decision making. The results indicate that simple infographics can help design professionals to better understand the health and safety implications of design decisions in the context of the construction site environment. In particular, the infographics appear to have increased designers’ ability to recognize less visible health and safety-related issues. The designers interviewed also described the potential usefulness of the infographics in design workshops as a tool to stimulate discussion and develop a shared understanding of the health and safety aspects of a particular design decision or choice. The value of the research lies in the development and evaluation of infographics as a tool supports the integration of health and safety into design decision making. The potential to develop these tools into digital or web-based resources is also significant.
Publisher: IGI Global
Date: 2012
Publisher: IEEE
Date: 02-2019
Publisher: Elsevier BV
Date: 11-2011
No related grants have been discovered for Andrew Stranieri.