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Статті в журналах з теми "Extraction des événements épidémiques"
Jun, Jennifer E. J., Angus Kinkade, Anthony C. H. Tung та Aaron M. Tejani. "5α-Reductase Inhibitors for Treatment of Benign Prostatic Hyperplasia: A Systematic Review and Meta-Analysis". Canadian Journal of Hospital Pharmacy 70, № 2 (28 квітня 2017). http://dx.doi.org/10.4212/cjhp.v70i2.1643.
Повний текст джерелаLeBras, Marlys H., and Arden R. Barry. "Influenza Vaccination for Secondary Prevention of Cardiovascular Events: A Systematic Review." Canadian Journal of Hospital Pharmacy 70, no. 1 (March 1, 2017). http://dx.doi.org/10.4212/cjhp.v70i1.1626.
Повний текст джерелаMihajlovic, Silvija, Jeremie Gauthier, and Erika MacDonald. "Patient Characteristics Associated with Adverse Drug Events in Hospital: An Overview of Reviews." Canadian Journal of Hospital Pharmacy 69, no. 4 (August 31, 2016). http://dx.doi.org/10.4212/cjhp.v69i4.1583.
Повний текст джерелаДисертації з теми "Extraction des événements épidémiques"
Mutuvi, Stephen. "Epidemic Event Extraction in Multilingual and Low-resource Settings." Electronic Thesis or Diss., La Rochelle, 2022. http://www.theses.fr/2022LAROS044.
Повний текст джерелаEpidemic event extraction aims to extract incidents of public health importance from text, such as disease outbreaks. While event extraction has been extensively researched for high-resource languages such as English, existing systems for epidemic event extraction are sub-optimal for low-resource, multilingual settings due to training data scarcity. First, we tackle the data scarcity challenge by transforming and annotating an existing document-level multilingual dataset into a token-level annotated dataset suitable for supervised sequence learning. Second, we formulate the event extraction task as a sequence labeling task and utilize the token-level annotated dataset to train supervised machine and deep learning models for epidemic event extraction. The results show that pre-trained language models produced the best overall performance across all the evaluated languages. Third, we propose a domain adaptation technique by including epidemiological entities (disease names and locations) in the vocabulary of pre-trained models. Incorporating the entities positively impacted the tokenization quality, contributing to model performance improvement. Finally, we evaluate self-training and observe that the approach performs marginally better than models trained using supervised learning
Arnulphy, Béatrice. "Désignations nominales des événements : étude et extraction automatique dans les textes." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00758062.
Повний текст джерелаEl, Khelifi Aymen. "Approche générique d’extraction automatique des événements et leur exploitation." Thesis, Paris 4, 2012. http://www.theses.fr/2012PA040189.
Повний текст джерелаIn the framework of our thesis, we proposed a generic approach for the automatic extraction of events and their exploitation. This approach is divided into four independent and reusable components. The first component of pretreatment, in which texts are cleaned and segmented. During the second stage, events are extracted based on our algorithm AnnotEC which has polynomial complexity. AnnotEC is associated with semantic maps and dedicated linguistic resources. We have proposed two new similarity measures SimCatégoreille and SimEvent to group similar events using clustering algorithms.Annotations, added throughout the first three steps, are used at the last component by summarizing files configurable by users. The approach was evaluated on a corpus of Web 2.0, we compared the obtained results with machine learning methods and linguistic compiling methods and we got good results
Ben, Salamah Janan. "Extraction de connaissances dans des textes arabes et français par une méthode linguistico-computationnelle." Thesis, Paris 4, 2017. http://www.theses.fr/2017PA040137.
Повний текст джерелаIn this thesis, we proposed a multilingual generic approach for the automatic information extraction. Particularly, events extraction of price variation and temporal information extraction linked to temporal referential. Our approach is based on the constitution of several semantic maps by textual analysis in order to formalize the linguistic traces expressed by categories. We created a database for an expert system to identify and annotate information (categories and their characteristics) based on the contextual rule groups. Two algorithms AnnotEC and AnnotEV have been applied in the SemanTAS platform to validate our assumptions. We have obtained a satisfactory result; Accuracy and recall are around 80%. We presented extracted knowledge by a summary file. In order to approve the multilingual aspect of our approach, we have carried out experiments on French and Arabic. We confirmed the scalability level by the annotation of large corpus
Erin, Macmurray. "Discours de presse et veille stratégique d'événements Approche textométrique et extraction d'informations pour la fouille de textes." Phd thesis, Université de la Sorbonne nouvelle - Paris III, 2012. http://tel.archives-ouvertes.fr/tel-00740601.
Повний текст джерелаAzouz, Nesrine. "Approches intelligentes pour le pilotage adaptatif des systèmes en flux tirés dans le contexte de l'industrie 4.0." Thesis, Université Clermont Auvergne (2017-2020), 2019. http://www.theses.fr/2019CLFAC028/document.
Повний текст джерелаToday, many production systems are managed in "pull" control system and used "card-based" methods such as: Kanban, ConWIP, COBACABANA, etc. Despite their simplicity and efficiency, these methods are not suitable when production is not stable and customer demand varies. In such cases, the production systems must therefore adapt the “tightness” of their production flow throughout the manufacturing process. To do this, we must determine how to dynamically adjust the number of cards (or e-card) depending on the context. Unfortunately, these decisions are complex and difficult to make in real time. In addition, in some cases, changing too often the number of kanban cards can disrupt production and cause a nervousness problem. The opportunities offered by Industry 4.0 can be exploited to define smart flow control strategies to dynamically adapt this number of kanban cards.In this thesis, we propose, firstly, an adaptive approach based on simulation and multi-objective optimization technique, able to take into account the problem of nervousness and to decide autonomously (or to help managers) when and where adding or removing Kanban cards. Then, we propose a new adaptive and intelligent approach based on a neural network whose learning is first realized offline using a twin digital model (simulation) and exploited by a multi-objective optimization method. Then, the neural network could be able to decide in real time, when and at which manufacturing stage it is relevant to change the number of kanban cards. Comparisons made with the best methods published in the literature show better results with less frequent changes
Частини книг з теми "Extraction des événements épidémiques"
CEA, Roberto. "Politique de santé entre concurrence scientifique et pouvoir des experts." In Les épidémies au prisme des SHS, 109–14. Editions des archives contemporaines, 2022. http://dx.doi.org/10.17184/eac.5996.
Повний текст джерела