130,599 research outputs found

    Health Technology Assessment. Konzepte, Methoden, Praxis für Wissenschaft und Entscheidungsfindung.

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    Perleth M, Busse R, Gerhardus A, Gibis B, Lühmann D, eds. Health Technology Assessment. Konzepte, Methoden, Praxis für Wissenschaft und Entscheidungsfindung. Berliner Schriftenreihe Gesundheitswissenschaften. Berlin: Medizinisch Wissenschaftlicher Verlag; 2008

    Die Effekte von HTA-Berichten im Gesundheitssystem.

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    Gerhardus A. Die Effekte von HTA-Berichten im Gesundheitssystem. In: Perleth M, Busse R, Gerhardus A, Gibis B, Lühmann D, eds. Health Technology Assessment. Konzepte, Methoden, Praxis für Wissenschaft und Entscheidungsfindung. Medizinisch Wissenschaftlicher Verlag; 2008: 58-62

    Die Bewertung sozio-kultureller Aspekte im HTA.

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    Gerhardus A. Die Bewertung sozio-kultureller Aspekte im HTA. In: Perleth M, Busse R, Gerhardus A, Gibis B, Lühmann D, eds. Health Technology Assessment. Konzepte, Methoden, Praxis für Wissenschaft und Entscheidungsfindung. Medizinisch Wissenschaftlicher Verlag; 2008: 197-202

    Projektmanagement von HTA-Berichten.

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    Schleberger H, Gerhardus A. Projektmanagement von HTA-Berichten. In: Perleth M, Busse R, Gerhardus A, Gibis B, Lühmann D, eds. Health Technology Assessment. Konzepte, Methoden, Praxis für Wissenschaft und Entscheidungsfindung. Medizinisch Wissenschaftlicher Verlag; 2008: 221-231

    Einführung: Bewertung der organisatorischen, rechtlichen, ethischen und sozio-kulturellen Aspekte von Technologien.

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    Gerhardus A. Einführung: Bewertung der organisatorischen, rechtlichen, ethischen und sozio-kulturellen Aspekte von Technologien. In: Perleth M, Busse R, Gerhardus A, Gibis B, Lühmann D, eds. Health Technology Assessment. Konzepte, Methoden, Praxis für Wissenschaft und Entscheidungsfindung. Medizinisch Wissenschaftlicher Verlag; 2008: 167-170

    Health Technology Assessment (HTA) und Prävention – passt das zusammen?

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    Gerhardus A, Lühmann D, Velasco-Garrido M, Walter U, Razum O. Health Technology Assessment (HTA) und Prävention – passt das zusammen? In: Kirch W, Badura B, Pfaff H, eds. Prävention und Versorgungsforschung. Berlin, Heidelberg: Springer; 2008: 35-61

    MeSH term explosion and author rank improve expert recommendations

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    Information overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

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