158,174 research outputs found

    User-centered visual analysis using a hybrid reasoning architecture for intensive care units

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    One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care

    Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches

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    Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements

    Using an Audience Response System Smartphone App to Improve Resident Education in the Pediatric Intensive Care Unit.

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    In the Pediatric Intensive Care Unit (PICU), most teaching occurs during bedside rounds, but technology now provides new opportunities to enhance education. Specifically, smartphone apps allow rapid communication between instructor and student. We hypothesized that using an audience response system (ARS) app can identify resident knowledge gaps, guide teaching, and enhance education in the PICU. Third-year pediatric residents rotating through the PICU participated in ARS-based education or received traditional teaching. Before rounds, experimental subjects completed an ARS quiz using the Socrative app. Concomitantly, the fellow leading rounds predicted quiz performance. Then, discussion points based on the incorrect answers were used to guide instruction. Scores on the pre-rotation test were similar between groups. On the post-rotation examination, ARS participants did not increase their scores more than controls. The fellow's prediction of performance was poor. Residents felt that the method enhanced their education whereas fellows reported that it improved their teaching efficiency. Although there was no measurable increase in knowledge using the ARS app, it may still be a useful tool to rapidly assess learners and help instructors provide learner-centered education

    Open, distributed and user-centered: Towards a paradigm shift in innovation policy

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    Today's innovation policies ignore that innovation is increasingly open, distributed and user-centered. In this paper we introduce the user-centered model as an alternative paradigm of how innovation 'works'. We discuss how it differs from traditional, linear producer-centered model, argue why it is legitimate to develop policies in support of it, and provide specific directions. �

    Software engineering (Encylopedia entry)

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