1,720,986 research outputs found
Connective tissue disease related fibrotic lung disease: high resolution computed tomographic and pulmonary function indices as prognostic determinants.
No full textTo determine high resolution computed tomography (HRCT) patterns and pulmonary function indices which are associated with increased mortality in patients with connective tissue disease related fibrotic lung disease (CTD-FLD).HRCTs from 168 patients with CTD-FLD were scored by 2 observers for a variety of HRCT patterns and traction bronchiectasis. A radiological diagnosis of usual interstitial pneumonia (UIP), fibrotic non-specific interstitial pneumonia (NSIP) or indeterminate was also assigned. Using Cox regression analysis, associations with mortality were identified. Honeycombing and traction bronchiectasis scores were converted to binary absence/presence scores and also tested. A subgroup analysis of patients with biopsy material (n=51) was performed by classifying patients according to radiological and histopathological diagnoses, as concordant UIP, discordant UIP and fibrotic NSIP. The prognostic separation of this classification was also evaluated.Severity of traction bronchiectasis (HR 1.10, p=0.001, 95\% CIs 1.04 to 1.17), increasing extent of honeycombing (HR 1.08, p=0.021, 95\% CI 1.03 to 1.13) and reduction in DLco (HR 0.97, p=0.013, 95\% CI 0.95 to 0.99) were independently associated with increased mortality. Interobserver agreement and prognostic strength were higher for binary traction bronchiectasis scores (weighted κ (κw)=0.69, HR 4.00, p=0.001, 95\%CI 1.19 to 13.38), than binary honeycombing scores (κw=0.50, HR 2.87, p=0.022, 95\% CI 1.53 to 5.43). The radiological-histopathological classification was strongly associated with increased mortality (HR 2.74, p<0.001, 95\% CI 1.57 to 4.77) and patients with discordant UIP had a better prognosis than concordant UIP but worse prognosis than fibrotic NSIP.Severity of traction bronchiectasis, extent of honeycombing and DLco are strongly associated with mortality in CTD-FLD. Interobserver agreement for traction bronchiectasis is higher than for honeycombing. In CTD-FLD, radiological diagnosis has survival implications in biopsy proven UIP
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Recognition, retrieval, and harmonisation for multicentre clinical data analysis
No full textArtificial Intelligence (AI) has emerged as a transformative force in medical imaging, significantly enhancing how professionals interpret complex data. Persistent issues mainly include (1) the inherent complexity and clinical variability of medical images, demanding highly adaptive AI for precise recognition and interpretation. (2) Developing effective AI solutions requires large, well-annotated datasets, a process that is time-consuming and resource-intensive for clinicians. (3) Research has largely concentrated on the preliminary stages such as diagnosis and feature extraction, neglecting the AI's potential for prognosis or long-term disease outcomes. (4) Variations in imaging devices, patient status, and protocol specifics limit the reproducibility and generalizability of AI models. This PhD program addresses these obstacles by concentrating on computational methods for clinical tasks such as recognition, retrieval, and data harmonization across multicenter datasets. Initial projects employed supervised learning to assess model performance in complex scenarios, including fine-grained recognition in kidney pathology and airway segmentation in lung CT scans. Innovations introduced include a fine-grained recognition model with uncertainty evaluation for differentiating different glomeruli and a fuzzy attention neural network enhanced by adversarial learning for more accurate airway segmentation, outperforming standard 3D segmentation approaches. To address the scarcity of annotated data, the research explored unsupervised learning with a novel deep mixture model that incorporates constraints to prevent segmentation errors. The AIIB23 challenge, held in conjunction with the MICCAI 2023 conference, established benchmarks for AI in airway segmentation and mortality prediction, helping to identify current research deficiencies. Furthermore, a clinical study involving patients with lung fibrosis compared the efficacy of image-derived biomarkers with conventional clinical metrics in mortality prediction, highlighting AI’s potential in clinical applications. The program also explored computational data harmonization, introducing an image retrieval system to categorize and align images based on textural similarities, promising advances for future large-scale clinical studies.Open Acces
Overview on Radiologic Patterns in Interstitial Lung Disease
No full textHigh resolution computed tomography (HRCT) plays a central role in the diagnostic process of interstitial lung disease (ILD). Although the HRCT findings usually correspond to recognizable chest radiography abnormalities, they are much more clearly identifiable on HRCT. In this chapter the role of chest radiography and HRCT in the diagnostic process of ILD are discussed. Main HRCT findings in ILD are described with a focus on specific situations where HRCT has a particular diagnostic importance and on the prognostic utility of specific CT patterns. The role of magnetic resonance imaging (MRI) and positron emission tomography (PET) in ILD patients is also discussed
Variations on the Author
Full text link“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
Full text linkWe 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
Full text linkWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe 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
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