115 resultados para Remote education

em Université de Lausanne, Switzerland


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The academic activities led by the Unit of Community Pharmacy can be classified as translational. Our group is interested in person-centered pharmaceutical services aimed at a more responsible use of drugs (effectiveness, safety, efficiency) in collaboration with physicians and other health care professionals in a primary care setting. The following domains of education and research are high priorities for our group: medication therapy management, medication adherence, integrated care, individualization of therapies, care management for the elderly and e-health.

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Prior research on school dropout has often focused on stable person- and institution-level variables. In this research, we investigate longitudinally perceived stress and optimism as predictors of dropout intentions over a period of four years, and distinguish between stable and temporary predictors of dropout intentions. Findings based on a nationally representative sample of 16e20 year-olds in Switzerland (N ¼ 4312) show that both average levels of stress and optimism as well as annually varying levels of stress and optimism affect dropout intentions. Additionally, results show that optimism buffers the negative impact of annually varying stress (i.e., years with more stress than usual), but not of stable levels of stress (i.e., stress over four years). The implications of the results are discussed according to a dynamic and preventive approach of school dropout.

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Background: Sponsoring of physicians meetings by life science companies has led to reduced participation fees but might influence physician's prescription practices. A ban on such sponsoring may increase participation fees. We aimed to evaluate factors associated with physicians' willingness to pay for medical meetings, their position on the sponsoring of medical meetings and their opinion on alternative financing options. Methods: An anonymous web-based questionnaire was sent to 447 general practitioners in one state in Switzerland, identified through their affiliation to a medical association. The questionnaire evaluated physicians' willingness to pay for medical meetings, their perception of a bias in prescription practices induced by commercial support, their opinion on the introduction of a binding legislation and alternative financing options, their frequency of exchange with sales representatives and other relevant socioeconomic factors. We built a multivariate predictor logistic regression model to identify determinants of willingness to pay. Results: Of the 115 physicians who responded (response rate 26%), 48% were willing to pay more than what they currently pay for congresses, 79% disagreed that commercial support introduced a bias in their prescription practices and 61% disagreed that it introduced a bias in their colleagues' prescription practices. Based on the multivariate logistic regression, perception of a bias in peers prescription practices (OR=7.47, 95% CI 1.65-38.18) and group practice structure (OR=4.62, 95% CI 1.34-22.29) were significantly associated with an increase in willingness to pay. Two thirds (76%) of physicians did not support the introduction of a binding legislation and 53% were in favour of creating a general fund administered by an independent body. Conclusion: Our results suggest that almost half of physicians surveyed are willing to pay more than what they currently pay for congresses. Predictors of an increase in physicians' willingness to pay were perception of the influence of bias in peers prescription practices and group practice structure. Most responders did not agree that sponsoring introduced prescribing bias nor did they support the 2 introduction of a binding legislation prohibiting sponsoring but a majority did agree to an independent body that would centrally administer a general fund.

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Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

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This manuscript has served for an oral presentation in honour of Professor Pierre Bovet who retired from his position as head physician at the Department of Psychiatry of the Lausanne University Hospital, Switzerland. Pierre Bovet has focused his clinical and scientific interest and his teaching activities on the schizophrenic spectrum disorders. The author tries to describe the essential elements of a clinical attitude which allows to really encounter the patient.

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