63 research outputs found

    Synchronous Gastric Tumours: Two Different Cases

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    Continuous professional development (CPD) in Periodontology refers to the overall framework of opportunities that facilitate a life-long learning practice, driven by the learner-practitioner and supported by a variety of institutions and individuals. CPD must address different needs for a great diversity of practitioners. It is clear that no particular methodology or technology is able to successfully accommodate the entire spectrum of CPD in Periodontology. Course designers must choose from and combine a wide array of methodologies and technologies, depending upon the needs of the learners and the objectives of the intended education. Research suggests that ‘interactivity’, ‘flexibility’, ‘continuity’ and ‘relevance to learners’ practice’ are major characteristics of successful CPD. Various methods of mentoring, peer-learning environments and work-based learning have been combined with reflective practice and self-study to form the methodological backbone of CPD courses. Blended learning encompasses a wide array of technologies and methodologies and has been successfully used in CPD courses. Internet-based content learning management systems, portable Internet devices, powerful databases and search engines, together with initiatives such as ‘open access’ and ‘open courseware’ provide an array of effective instructional and communication tools. Assessment remains a key issue in CPD, providing learners with valuable feedback and it ensures the credibility and effectiveness of the learning process. Assessment is a multi-level process using different methods for different learning outcomes, as directed by current evidence and best practices. Finally, quality assurance of the education provided must follow CPD courses at all times through a structured and credible process

    Significance testing as perverse probabilistic reasoning

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    Truth claims in the medical literature rely heavily on statistical significance testing. Unfortunately, most physicians misunderstand the underlying probabilistic logic of significance tests and consequently often misinterpret their results. This near-universal misunderstanding is highlighted by means of a simple quiz which we administered to 246 physicians at two major academic hospitals, on which the proportion of incorrect responses exceeded 90%. A solid understanding of the fundamental concepts of probability theory is becoming essential to the rational interpretation of medical information. This essay provides a technically sound review of these concepts that is accessible to a medical audience. We also briefly review the debate in the cognitive sciences regarding physicians' aptitude for probabilistic inference

    Inferring human values for safe AGI design

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    Due to copyright restrictions, the access to the full text of this article is only available via subscription.Aligning goals of superintelligent machines with human values is one of the ways to pursue safety in AGI systems. To achieve this, it is first necessary to learn what human values are. However, human values are incredibly complex and cannot easily be formalized by hand. In this work, we propose a general framework to estimate the values of a human given its behavior

    Post Covid-19 and business analytics

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    This paper highlights the way companies can apply artificial intelligence (AI) in the post Covid-19 period. We show that how the AI can be advantageous to develop an inclusive model and apply to the businesses of various sizes. The recommendation can be beneficial for academic researchers to identify several ways to overcome the obstacles that companies may face in post Covid-19 period. The paper also addresses few major global issues, which can assist the policy makers to consider developing a business model to bounce back the world economy after this crisis is over. Overall, this paper enhances the understanding of stakeholders of business about the importance of application of the AI in businesses in a volatile market in post Covid-19 period
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