141 resultados para Historical series


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Internationally, policies for attracting highly-skilled migrants have become the guidelines mainly used by the Organisation for Economic Co-operation and Development (OECD) countries. Governments are implementing specific procedures to capture and facilitate their mobility. However, all professions are not equal when it comes to welcoming highly-skilled migrants. The medical profession, as a protective market, is one of these. Taking the case of non-EU/EEA doctors in France, this paper shows that the medical profession defined as the closed labour market, remains the most controversial in terms of professional integration of migrants, protectionist barriers to migrant competition and challenge of medical shortage. Based on the path-dependency approach, this paper argues that non-EU/EEA doctors' issues in France derive from a complex historical process of interaction between standards settled in the past, particularly the historical power of medical corporatism, the unexpected long-term effects of French hospital reforms of 1958, and budgetary pressures. Theoretically, this paper shows two significant findings. Firstly, the French medical system has undergone a series of transformations unthinkable in the strict sense of a path-dependence approach: an opening of the medical profession to foreign physicians in the context of the Europeanisation of public policy, acceptance of non-EU/EEA doctors in a context of medical shortage and budgetary pressures. Secondly, there is no change of the overall paradigm: significantly, the recruitment policies of non-EU/EEA doctors continue to highlight the imprint of the past and reveal a significant persistence of prejudices. Non-EU/EEA doctors are not considered legitimate doctors even if they have the qualifications of physicians which are legitimate in their country and which can be recognised in other receiving countries.

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Study design: A retrospective study of image guided cervical implant placement precision. Objective: To describe a simple and precise classification of cervical critical screw placement. Summary of Background Data: "Critical" screw placement is defined as implant insertion into a bone corridor which is surrounded circumferentially by neurovascular structures. While the use of image guidance has improved accuracy, there is currently no classification which provides sufficient precision to assess the navigation success of critical cervical screw placement. Methods: Based on postoperative clinical evaluation and CT imaging, the orthogonal view evaluation method (OVEM) is used to classify screw accuracy into grade I (no cortical breach), grade la (screw thread cortical breach), grade II (internal diameter cortical breach) and grade III (major cortical breach causing neural or vascular injury). Grades II and III are considered to be navigation failures, after accounting for bone corridor / screw mismatch (minimal diameter of targeted bone corridor being smaller than an outer screw diameter). Results: A total of 276 screws from 91 patients were classified into grade I (64.9%), grade la (18.1%), and grade II (17.0%). No grade III screw was observed. The overall rate of navigation failure was 13%. Multiple logistic regression indicated that navigational failure was significantly associated with the level of instrumentation and the navigation system used. Navigational failure was rare (1.6%) when the margin around the screw in the bone corridor was larger than 1.5 mm. Conclusions: OVEM evaluation appears to be a useful tool to assess the precision of critical screw placement in the cervical spine. The OVEM validity and reliability need to be addressed. Further correlation with clinical outcomes will be addressed in future studies.

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The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.

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Thrombosis is a well known phenomenon among physicians since antiquity. A variety of peculiar agents, such as leeches and bark, were used to prevent it. Hirudin was used during the 19th century. The next eon, heparin, strepokinase, urokinase, TPA, dicumarol, warfarin, aspirin, ticlopidine, Clopidogrel, SSHA and SP54 provoked huge advances in anticoagulation. During 21st century with the use of fondaparinux, dabigatran, rivaroxaban and Ticagrelor antithrombotic prevention and therapeutic interaction entered an era of medical challenges. Although the risk after a thrombotic episode is now highly reduced, blood clots still present damaging or even lethal consequences in human organisms and further research is strongly recommended.