Evaluation of the quality of the management of cancer of the corpus uteri-Selection of relevant quality indicators and implementation in Belgium

Objective Describe the methodology and selection of quality indicators (QI) to be implemented in the EFFECT (EFFectiveness of Endometrial Cancer Treatment) project. EFFECT aims to monitor the variability in Quality of Care (QoC) of uterine cancer in Belgium, to compare the effectiveness of different treatment strategies to improve the QoC and to check the internal validity of the QI to validate the impact of process indicators on outcome. Methods A QI list was retrieved from literature, recent guidelines and QI databases. The Belgian Healthcare Knowledge Center methodology was used for the selection process and involved an expert's panel rating the QI on 4 criteria. The resulting scores and further discussion resulted in a final QI list. An online EFFECT module was developed by the Belgian Cancer Registry including the list of variables required for measuring the QI. Three test phases were performed to evaluate the relevance, feasibility and understanding of the variables and to test the compatibility of the dataset. Results 138 QI were considered for further discussion and 82 QI were eligible for rating. Based on the rating scores and consensus among the expert's panel, 41 QI were considered measurable and relevant. Testing of the data collection enabled optimization of the content and the user-friendliness of the dataset and online module. Conclusions This first Belgian initiative for monitoring the QoC of uterine cancer indicates that the previously used QI selection methodology is reproducible for uterine cancer. The QI list could be applied by other research groups for comparison. © 2013 Elsevier Inc.

Traitement de données issues d'un corpus écrit multilingue. Approche agile pour l'analyse du discours eurorégional

L'article présente quelques éléments de la procédure mise en place pour traiter un corpus écrit comportant 617 textes (près de 500 000 mots) relatifs aux eurorégions. Complexe et hétérogène à plusieurs titres (technique, linguistique, éditorial, générique, énonciatif), le corpus pose la difficulté majeure de l’appréhension de données multilingues (français, italien, espagnol, anglais, allemand, néerlandais). Sa manipulation a nécessité une réflexion adaptée et une démarche de modélisation que nous qualifions d’« agile » en raison de son caractère souple et itératif. La plateforme d’analyse élaborée permet de disposer de résultats utiles à l’analyse qualitative ultérieure du discours eurorégional. Elle articule un logiciel d'analyse morphosyntaxique éprouvé (TreeTagger) à des programmes (Perl) et à une base de données (SQLite) développés pour optimiser les requêtes multilingues simultanées et l’exportation automatique des résultats. Les fonctionnalités liées à la localisation contextualisée de mots- pivots, au recueil de dénominations et à la détection de segments répétés nous servent ici de guides pour exprimer les besoins de la recherche, les problèmes rencontrés et les solutions proposées. L'analyse d'observables récurrents, à savoir les notions de décision et de responsabilité, illustre le propos.

La formation discursive eurorégionale. Articulation et approche sémantique d’un corpus multilingue

L’objectif de cet article est double :il s’agit, d’une part, de présenter un nouveau corpus permettant d’envisager le phénomène émergent de la communication transfrontalière en Europe et, d’autre part, de formuler trois questionnements utiles au cadrage de son analyse sémantique. À partir du corpus eurorégional – multilingue et multigenre - nous posons les questions de la dispersion des discours en ligne, de l’hétérogénéité des données et de la contextualisation de l’analyse. Notre démarche consiste à construire progressivement un modèle d’analyse adapté à l’appréhension, tantôt automatique et tantôt manuelle, de la diversité des textes. Enfin, nous proposons d’illustrer la démarche en l’appliquant à la mobilité, observable récurrent du corpus.

Annotating an Oral Corpus using the Text Encoding Initiative. Methodology, Problems, Solutions

The objective of this paper is to describe and evaluate the application of the Text Encoding Initiative (TEI) Guidelines to a corpus of oral French, this being the first corpus of oral French where the TEI has been used. The paper explains the purpose of the corpus, both in creating a specialist corpus of néo-contage that will broaden the range of oral corpora available, and, more importantly, in creating a dataset to explore a variety of oral French that has a particularly interesting status in terms of factors such as conception orale/écrite, réalisation médiale and comportement communicatif (Koch and Oesterreicher 2001). The linguistic phenomena to be encoded are both stylistic (speech and thought presentation) and syntactic (negation, detachment, inversion), and all represent areas where previous research has highlighted the significance of factors such as medium, register and discourse type, as well as a host of linguistic factors (syntactic, phonetic, lexical). After a discussion of how a tagset can be designed and applied within the TEI to encode speech and thought presentation, negation, detachment and inversion, the final section of the paper evaluates the benefits and possible drawbacks of the methodology offered by the TEI when applied to a syntactic and stylistic markup of an oral corpus.

Creating a spontaneous conversational speech corpus

Speech recognition and language analysis of spontaneous speech arising in naturally spoken conversations are becoming the subject of much research. However, there is a shortage of spontaneous speech corpora that are freely available for academics. We therefore undertook the building of a natural conversation speech database, recording over 200 hours of conversations in English by over 600 local university students. With few exceptions, the students used their own cell phones from their own rooms or homes to speak to one another, and they were permitted to speak on any topic they chose. Although they knew that they were being recorded and that they would receive a small payment, their conversations in the corpus are probably very close to being natural and spontaneous. This paper describes a detailed case study of the problems we faced and the methods we used to make the recordings and control the collection of these social science data on a limited budget.

Gastric corpus atrophy following eradication of Helicobacter pylori

Atrophic gastritis can develop in patients with Helicobacter pylori infection leading to a reduction in basal acid output. Whether the atrophy that develops is reversible is controversial.

A Corpus-Based Approach to Speech Enhancement from Nonstationary Noise

Temporal dynamics and speaker characteristics are two important features of speech that distinguish speech from noise. In this paper, we propose a method to maximally extract these two features of speech for speech enhancement. We demonstrate that this can reduce the requirement for prior information about the noise, which can be difficult to estimate for fast-varying noise. Given noisy speech, the new approach estimates clean speech by recognizing long segments of the clean speech as whole units. In the recognition, clean speech sentences, taken from a speech corpus, are used as examples. Matching segments are identified between the noisy sentence and the corpus sentences. The estimate is formed by using the longest matching segments found in the corpus sentences. Longer speech segments as whole units contain more distinct dynamics and richer speaker characteristics, and can be identified more accurately from noise than shorter speech segments. Therefore, estimation based on the longest recognized segments increases the noise immunity and hence the estimation accuracy. The new approach consists of a statistical model to represent up to sentence-long temporal dynamics in the corpus speech, and an algorithm to identify the longest matching segments between the noisy sentence and the corpus sentences. The algorithm is made more robust to noise uncertainty by introducing missing-feature based noise compensation into the corpus sentences. Experiments have been conducted on the TIMIT database for speech enhancement from various types of nonstationary noise including song, music, and crosstalk speech. The new approach has shown improved performance over conventional enhancement algorithms in both objective and subjective evaluations.