1,721,326 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
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
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Nasale CPAP bij slaapgebonden ademhalingsstoornissen: pati\uebntenprofiel, therapiecompliance en invloed op de gasuitwisseling en het longfunctiepatroon
koamabayili/VECTRON-author-checklist: VECTRON author checklist
We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Artificial intelligence in functional respiratory imaging : opening the black box
Abstract: Current medical practice within pulmonology focuses on outdated spirometry methods such as pulmonary function tests. Seeing these tests are bulk measures, they don\u2019t show any regional information of the lungs, and they are subject to significant intrinsic variability and uncertainty. This eventually leads to false diagnoses and non-optimized treatment in patients. Furthermore, disease progression and effects of medical interventions are usually studied on a population level, which makes it hard to draw conclusions for patient-specific cases. FLUIDDA has developed Functional Respiratory Imaging (FRI), which combines computational fluid dynamics and biomedical imaging techniques. FLUIDDA's proprietary FRI technology allows for visualization and quantification of regional lung structures and lung function, enabling characterization of lung health with more sensitive endpoints. FRI has been used extensively to both map disease progression, as well as study effects of medical interventions on a population level, but extrapolation of those results to patient-specific strategies was not established yet. In this work, the possibilities of combining FRI with artificial intelligence, and more specifically, machine learning applications were studied, to ensure more optimized patient-specific diagnoses, treatments and follow-up. FRI endpoints were first tested for their sensitivity, by studying the effects of bronchodilators in asthma and COPD patients with both FRI and standard spirometry endpoints. From the results it showed that FRI parameters were substantially more sensitive, which makes them ideal input parameters for machine learning applications. Two types of machine learning projects were established, i.e. prediction of patient-specific disease progression and responder phenotyping for medical treatments. In a first project, imminent exacerbations in COPD patients could be predicted with an accuracy of 80%. For a second project, responders to a new compound for IPF treatment could be identified with an accuracy of 86.5%. Finally, in the last machine learning project, lung transplant rejection could be predicted with an accuracy of 85%. With this work it has been proven that in the respiratory space as well, artificial intelligence algorithms in combination with comprehensive imaging endpoints allow for the creation of very robust predictive models, enabling major potential for well-established, patient-specific diagnosis, follow-up and treatment
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