Titlebook: Knowledge Representation for Health-Care; AIME 2011 Workshop K David Ria?o,Annette Teije,Silvia Miksch Conference proceedings 2012 Springer

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Joan Albert López-Vallverdú,David Ria?o,Antoni Colladon for Economic Co-operation and Development (OECD) countries where structural unemployment appears to have increased significantly since the early 1990s (Brandt .., 2005, p. 6). If effective solutions can be found to overcome these abject circumstances, then not only will the economic situation impr

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Paul Taylor,Igor Toujilov. Second, that since 1974 up to the takeover of its mandate by the Eurosystem in 1999 it almost exclusively (apart from the Swiss National Bank — SNB) stuck to what has been labelled ‘monetary targeting’. Do these two aspects bear any relationship to each other? This is the question I will try to an

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. Second, that since 1974 up to the takeover of its mandate by the Eurosystem in 1999 it almost exclusively (apart from the Swiss National Bank — SNB) stuck to what has been labelled ‘monetary targeting’. Do these two aspects bear any relationship to each other? This is the question I will try to an

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The “Human Cli-Knowme” Project: Building a Universal, Formal, Procedural and Declarative Clinical Knical informatics is .. The required knowledge consists of both . knowledge, such as clinical guidelines, and . knowledge, such as context-sensitive interpretations of longitudinal patterns of raw clinical data accumulating from several sources..In this position paper, I first demonstrate the feasibi

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A Systematic Analysis of Medical Decisions: How to Store Knowledge and Experience in Decision Tableson medical knowledge and the physician’s experience, among other factors. In this paper, we first present a set of key questions that involve clinical decisions and that are faced by medical practitioners in a daily basis. We then discuss the type and codification of the information needed to answer

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Task Network Based Modeling, Dynamic Generation and Adaptive Execution of Patient-Tailored Treatmentinical decisions and clinical processes execution in the field of pediatric oncology treatments. The system builds on a previous proof of concept devoted to demonstrate that Hierarchical Planning and Scheduling is an enabling technology to support clinical decisions. The present work describes new i

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Careflow Personalization Services: Concepts and Tool for the Evaluation of Computer-Interpretable Gued according to the patient’s health state, but also takes into account implicit information (e.g., patients’ preferences, local restrictions, etc). It may demand huge efforts, is error prone and the resulting guideline can contain contradictions. In this sense, Computer-Interpretable Guidelines ass