1,720,993 research outputs found
Challenges of human scored cleft aesthetic outcome evaluation: a critical review of literature and exploration of the potential for applying AI to analyse routinely collected global data
Full text linkBACKGROUND:
Orofacial clefts are the commonest type of congenital anomaly to affect the craniofacial region, affecting approximately 1 in 700 live births in the UK, with higher incidences in low-middle income countries. Surgical repair of cleft lip and/or palate is usually performed in infancy; however, there are concerning inequalities in access to and quality of surgical care, and few global outcome studies. Scoring aesthetic results after surgery is crucial when determining the success of a repair, and helps to distinguish between advantageous and unfavourable approaches. Currently, a reliable and accurate scoring system utilising large numbers of unstandardised 2- dimentional photographs of patients from varying ethnic backgrounds, which is inexpensive, widely accepted and easily applicable, does not exist. Artificial Intelligence (AI) has been applied in a variety of specialities of medicine and surgery with beneficial results; however, its advantages have not yet been harnessed in cleft care.
OBJECTIVES:
This thesis had three primary objectives:
1. Toidentifytheproblemswiththepre-operativecleftseverityandpost-
operative aesthetic scoring systems currently used in the management of
cleft lips.
2. Inlightofthelimitationsofthecurrentmethods(specificallysurrounding
human assessment), to consider the potential benefits and pitfalls of using
AI in order to develop a robust reproducible scoring system.
3. ToevaluateanddescriberoutinelycollecteddatafromtheglobalSmile
Train dataset (STX) and prepare the data for AI analysis.
METHODS:
1. Toachievethefirstobjective,acriticalsurveyoftheliteratureconcerning pre-operative cleft severity grading and post-operative aesthetic outcome evaluation methods for cleft lip was undertaken.
2. AcriticalsurveyoftheliteraturerelevanttotheapplicationofAItosimilar challenges in medicine, in particular cleft and plastic surgery, was undertaken. The review focused on facial image analysis, the importance of ethical use, and minimising the risk of algorithmic bias.
3. Adatamanagementplanwascreatedforthetransferandstorageof demographic and image data from STX for over 1.5 million patients. Data were checked for accuracy and consistency. Demographic and diagnostic data were studied to determine inclusion and exclusion criteria. A dataset of images labelled with the diagnosis was created for AI analysis.
CONCLUSIONS:
A review of the literature demonstrated that current scoring methods lack sizeable datasets, ethnic diversity and applicable techniques in resource-limited centres, and there is need for an innovative globally applicable scoring system to evaluate aesthetic outcomes. Doing this will enable international comparative studies and audit/quality control with rapid closure of the audit loop, ultimately minimising inequalities and improving cleft care. AI can be used to analyse the dataset in preparation for future research when evaluating aesthetic outcomes.
This study shows that, despite some challenges, it is possible to study routinely collected global data, thus enabling the application of AI to large datasets. Additionally, this study is able to make some recommendations to Smile Train for more robust data collection in the future
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
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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