1,720,978 research outputs found
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
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
Risk stratification in patients with secondary valvular heart disease and heart failure
No full textHintergrund und Ziele: Die sekundäre Mitral- (sMI) und Trikuspidalklappeninsuffizienz (sTI) zählen zu den häufigsten Herzklappenvitien in Herzinsuffizienzpatienten (HI) und erhöhen signifikant die Mortalität. Aufgrund der alternden Bevölkerungsstruktur und der steigenden Herzinsuffizienzprävalenz, ist hier von einer großen Belastung für Gesundheitssysteme auszugehen. Technologische Fortschritte in kathetergestützten Behandlungsverfahren, wie die so genannten transkatheter edge-to-edge Reparatur, bieten hier einer Option mit niedrigem Risiko. Dennoch zeigen randomisierte Studien in der Therapie der sMI divergierende Ergebnisse in Bezug auf Überleben und es findet sich eine sehr niedrige Behandlungsrate von sMI und sTI. Dies zeigt, dass die derzeitige Risikostratifizierung unzureichend ist und dass eine Notwendigkeit zur verbesserten Patientenselektion basierend auf morphologischen Parametern und Biomarkern besteht. Ziel war es die Beschreibung von Phänotypen und die Risikostratifizierung in Patienten mit HI und sekundären Herzklappenvitien zu verbessern.Methoden: Es wurde eine umfassende morphologische und funktionelle Netzwerkanalyse unter der Verwendung von zahlreichen echokardiographischen Parametern in prospektiv rekrutierten sMI-Patienten mit stabiler HI durchgeführt. Hierfür wurde eine Hauptkomponentenanalyse, um die wichtigsten morphologischen Komponenten zu finden, verwendet. Anschließend wurden mittels Clustering morphologische Phänotypen gesucht. Ergänzend wurden in großen Datensätzen der spezifische Zielpopulationen Techniken des überwachten Lernens, nämlich Überlebens – Entscheidungsbäume verwendet, um Hochrisiko-Subgruppen in Patienten mit HI und höhergradiger sMI zu identifizieren. In Patienten mit mittel- und höhergradiger sTI wurde eine optimierte Risikostratifizierung entwickelt unter der Verwendung von „Randomforest“-Modellen. Die Patienten wurden anhand der Anzahl ihrer ungünstigen Merkmale gruppiert. Resultate: Zwei morphologische Hauptkomponenten mit einer signifikanten Assoziation zur sMI-Schwere konnten identifiziert werden. Diese spiegeln das linke Atrium und den linken Ventrikel wider. Weiters wurden vier morphologisch distinkte Phänotypen, die signifikanten Einfluss auf die Patientenprognose hatten, gefunden. Überwachtes Lernen zeigte zudem acht unterschiedliche sMI-Subgruppen, wobei Hochrisiko-Gruppen ein bis zu 20-fach erhöhtes Mortalitätsrisiko hatten. Diese wurden durch höheres Alter, niedrigeres Serumalbumin und stärkere neurohumorale Aktivierung definiert. In der sTI konnten Patienten nach der Anzahl der Prädiktoren mit der höchsten Assoziation zur Mortalität gruppiert werden. Patienten mit mittelgradiger sTI und vier oder mehr ungünstigen Prädiktoren hatten ein 4-fach erhöhtes Mortalitätsrisiko, bei Patienten mit höhergradiger sTI war die Mortalität 5-fach erhöht. Dieses Vorgehen resultierte in relevanter prognostischer Information. Schlussfolgerung: Die Risikostratifizierung in sekundären Herzklappenvitien ist aufgrund eines sehr heterogenen Risikospektrums der Patienten herausfordernd. Durch Analyse der morphologischen Aspekte lassen sich in der sMI klinisch relevante Phänotypen identifizieren. Mit Überlebens – Entscheidungsbäumen können Hochrisiko-Subgruppen in HI Patienten mit sMI dargestellt werden und die Risikostratifizierung in der sTI wurde optimiert um den klinischen Entscheidungsprozess und das Patientenmanagement zu unterstützen.Background and aims: Secondary mitral (sMR) and tricuspid regurgitation (sTR) are common valvular disorders in patients with heart failure (HF) and have significant adverse impact on the patient’s prognosis. Population aging and increasing HF prevalence indicate a major burden for health care systems. Technological advances in transcatheter-based treatment options, such as transcatheter edge-to-edge repair, now offer low-risk treatment options for these vulnerable patients. Diverging results of randomized studies and reported undertreatment in cohort studies indicate an unmet clinical need for improved patient selection and decision-making based on morphomic- and biomarker phenotyping. The aim of the thesis was therefore to improve characterization of phenotypes and refine risk stratification in patients with secondary valvular regurgitation and HF. Methods: In a cohort of prospectively recruited patients with heart failure morphological and functional network profiling was conducted using advanced echocardiographic morphological and functional parametric assessment in patients with sMR and chronic HF. Principal component analysis was performed to investigate the main morphological components in sMR. Subsequent cluster analysis was used to explore morphological phenotypes. Complementary analyses from large datasets in specific target populations by supervised machine learning techniques, namely survival trees, were utilized to examine high risk subgroups in severe sMR and HF. In moderate and severe sTR a streamlined risk stratification was developed according to the patient’s number of adverse features using random survival forest techniques. Results: Two main morphological components with significant association to sMR severity were identified, representing the left atrium and left ventricle. Furthermore, 4 morphologically distinct clusters with significant prognostic impact were found. Using supervised machine learning in severe sMR and HF revealed 8 distinct subgroups, with a 20-fold risk increase in high-risk subgroups, defined by higher age, low albumin levels and higher neurohumoral activation. In sTR, patients were grouped according to the number of predictors with the highest association to mortality. Patients with four or more adverse features had a 4-fold risk increase in mortality in moderate and 5-fold increase in severe sTR. This approach to risk stratification added significant prognostic information.Conclusion: Risk stratification in sMR and sTR is challenging due to a heterogenous risk spectrum of patients. Morphologic components in sMR allow identification of clinically significant phenotypes and survival trees in severe sMR delineate high risk subgroups. Risk stratification in sTR can be streamlined to aid clinical decision making and optimize patient care.Abweichender Titel laut Übersetzung der Verfasserin/des VerfassersDissertation Medizinische Universität Wien 202
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
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