1,721,037 research outputs found
Towards standardised radiologic evaluation and reporting of acute traumatic brain injuries
No full textAbstract: Neuroimaging techniques play a pivotal role in the diagnosis and follow-up of patients with Traumatic Brain Injury (TBI). Imaging findings determine patient management and influence the clinical course. Unfortunately, conventional evaluation of imaging studies and free-text radiologic reporting is problematic in patients with TBI, mainly due to the significant differences in content, length, style and language of the generated radiology reports. Moreover, there is substantial inter-observer variation in how pathology is characterised, even between experts. In order to advance clinical decision-making and research into TBI, a more complete, precise and consistent characterisation of brain pathology was urgently needed. In 2010, a multidisciplinary task force, under the aegis of the National Institute of Health (NIH) and the National Institute of Neurological Disorders and Stroke (NINDS), created a framework for a more structured way of radiologic reporting in clinical trials, by providing a standardised language of "common data elements" (CDEs). Despite the many presumed benefits of this standardised framework, a thorough investigation and validation was still lacking. We performed a standardised central radiology review, based on the NIH/NINDS CDEs, on over 4,000 acute non-contrast computed tomography (NCCT) scans, uploaded to a central imaging database for the large pan-European CENTER-TBI study. We explored inter- and intra-observer agreement, compared centralised versus local assessment, and we created regularised logistic regression models to investigate the prognostic relevance of the different NIH/NINDS CDEs. In addition, we also developed and tested machine learning algorithms, intended to objectively quantify relevant imaging characteristics. Our results indicate that on-site radiologic evaluation and reporting suffers from substantial inconsistencies, which is highly detrimental in multi-centre studies. Conversely, we showed that an independent central radiology review process, using NIH/NINDS CDEs, offers a more consistent way of characterising pathology, with high levels of inter-and intra-observer agreement. We also demonstrated that, on a large scale, this kind of characterisation allows for extensive data mining and the development of strong clinical predictive models. Furthermore, our automated machine learning-based approach achieved good performance for the segmentation of lesion volumes, cisternal volumes, and midline shift measurement. In conclusion, our work shows that standardised radiologic evaluation and reporting, using the NIH/NINDS CDEs, combined with automation of certain aspects of radiologic evaluation, is very promising and can significantly advance clinical research. Based on our findings, we made recommendations for clinical radiology reporting, and developed an image interpretation checklist, accompanied by a comprehensive and fully illustrated patho-anatomic atlas, with over 200 images from the CENTER-TBI study. Our efforts can help physicians and researchers to reliably and reproducibly interpret NCCT scans of brain-injured patients, thus paving the way towards a more globally accepted standardised evaluation and reporting of acute traumatic brain injuries
Characterization of biophysical stromal properties in human cancer : towards personalized computational oncology
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Editorial for 'Characterizing streamline count invariant graph measures of structural connectomes'
No full textGoing Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
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