4,003 research outputs found

    Using language technologies to support individual formative feedback

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    In modern educational environments for group learning it is often challenging for tutors to provide timely individual formative feedback to learners. Taking the case of undergraduate Medicine, we have found that formative feedback is generally provided to learners on an ad-hoc basis, usually at the group, rather than individual, level. Consequently, conceptual issues for individuals often remain undetected until summative assessment. In many subject domains, learners will typically produce written materials to record their study activities. One way for tutors to diagnose conceptual development issues for an individual learner would be to analyse the contents of the learning materials they produce, which would be a significant undertaking. CONSPECT is one of six core web-based services of the Language Technologies for Lifelong Learning (LTfLL) project. This European Union Framework 7-funded project seeks to make use of Language Technologies to provide semi-automated analysis of the large quantities of text generated by learners through the course of their learning. CONSPECT aims to provide formative feedback and monitoring of learners’ conceptual development. It uses a Natural Language Processing method, based on Latent Semantic Analysis, to compare learner materials to reference models generated from reference or learning materials. This paper provides a summary of the service development alongside results from validation of Version 1.0 of the service

    Government policy and healthcare management: proposal of a shared decision-making model

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    As a consequence of the current economic crisis many changes have been introduced to health systems on national levels to reduce expenditure and to introduce more cost-effective methods. Then recent developments in medical technology have led to a shift in the traditional framework of physician-patient responsibility in health care decision making. In this context, the health community urges, in any case, decision makers to ensure that all changes introduced are in accordance with Health System Values. This paper presents a new decision making platform, as a tool to facilitate shared decision making, to improve the quality and transparency of tactical and strategic decisions. This new application, based on analytic quantitative method, is a component of a wider distribute web system under development, which aims to inform the new effective health technologies supporting designers in the user need elicitation and early stage health technology assessments. A case study aiming to elicit the user needs affecting the decision of whether to adopt a new magnetic resonance imaging (MRI) is also presented

    Biomedical Knowledge Engineering Using a Computational Grid

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    Developing Ontologies withing Decentralized Settings

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    This chapter addresses two research questions: “How should a well-engineered methodology facilitate the development of ontologies within communities of practice?” and “What methodology should be used?” If ontologies are to be developed by communities then the ontology development life cycle should be better understood within this context. This chapter presents the Melting Point (MP), a proposed new methodology for developing ontologies within decentralised settings. It describes how MP was developed by taking best practices from other methodologies, provides details on recommended steps and recommended processes, and compares MP with alternatives. The methodology presented here is the product of direct first-hand experience and observation of biological communities of practice in which some of the authors have been involved. The Melting Point is a methodology engineered for decentralised communities of practice for which the designers of technology and the users may be the same group. As such, MP provides a potential foundation for the establishment of standard practices for ontology engineering

    An Ontology Approach for Knowledge Acquisition and Development of Health Information System (HIS)

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    This paper emphasizes various knowledge acquisition approaches in terms of tacit and explicit knowledge management that can be helpful to capture, codify and communicate within medical unit. The semantic-based knowledge management system (SKMS) supports knowledge acquisition and incorporates various approaches to provide systematic practical platform to knowledge practitioners and to identify various roles of healthcare professionals, tasks that can be performed according to personnel’s competencies, and activities that are carried out as a part of tasks to achieve defined goals of clinical process. This research outcome gives new vision to IT practitioners to manage the tacit and implicit knowledge in XML format which can be taken as foundation for the development of information systems (IS) so that domain end-users can receive timely healthcare related services according to their demands and needs

    User needs elicitation via analytic hierarchy process (AHP). A case study on a Computed Tomography (CT) scanner

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    Background: The rigorous elicitation of user needs is a crucial step for both medical device design and purchasing. However, user needs elicitation is often based on qualitative methods whose findings can be difficult to integrate into medical decision-making. This paper describes the application of AHP to elicit user needs for a new CT scanner for use in a public hospital. Methods: AHP was used to design a hierarchy of 12 needs for a new CT scanner, grouped into 4 homogenous categories, and to prepare a paper questionnaire to investigate the relative priorities of these. The questionnaire was completed by 5 senior clinicians working in a variety of clinical specialisations and departments in the same Italian public hospital. Results: Although safety and performance were considered the most important issues, user needs changed according to clinical scenario. For elective surgery, the five most important needs were: spatial resolution, processing software, radiation dose, patient monitoring, and contrast medium. For emergency, the top five most important needs were: patient monitoring, radiation dose, contrast medium control, speed run, spatial resolution. Conclusions: AHP effectively supported user need elicitation, helping to develop an analytic and intelligible framework of decision-making. User needs varied according to working scenario (elective versus emergency medicine) more than clinical specialization. This method should be considered by practitioners involved in decisions about new medical technology, whether that be during device design or before deciding whether to allocate budgets for new medical devices according to clinical functions or according to hospital department
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