Search results for ""Author Matthew Thompson""

Diagnostic Tests Toolkit Diagnostic Tests Toolkit Finding the evidence for diagnostic tests Establishing an evidence-based methodology to assess the effectiveness of diagnostic tests has posed problems for many years. Now that the framework is in place health professionals can find and appraise the evidence for themselves. With Diagnostic Tests Toolkit clinicians and junior researchers can interpret the evidence for the effectiveness of different types of diagnostic tests, or develop their own research using the successful ‘step-by-step’ format of the Toolkit series. Written by renowned clinical researchers, this is the first basic guide to evidence-based diagnosis. It is equally valuable to starters in clinical research and those needing a quick refresher on the core elements of evidence-based diagnosis.

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Uncertainties are pervasive in natural hazards, and it is crucial to develop robust and meaningful approaches to characterize and communicate uncertainties to inform modeling efforts. In this monograph we provide a broad, cross-disciplinary overview of issues relating to uncertainties faced in natural hazard and risk assessment. We introduce some basic tenets of uncertainty analysis, discuss issues related to communication and decision support, and offer numerous examples of analyses and modeling approaches that vary by context and scope. Contributors include scientists from across the full breath of the natural hazard scientific community, from those in real-time analysis of natural hazards to those in the research community from academia and government. Key themes and highlights include: Substantial breadth and depth of analysis in terms of the types of natural hazards addressed, the disciplinary perspectives represented, and the number of studies included Targeted, application-centered analyses with a focus on development and use of modeling techniques to address various sources of uncertainty Emphasis on the impacts of climate change on natural hazard processes and outcomes Recommendations for cross-disciplinary and science transfer across natural hazard sciences This volume will be an excellent resource for those interested in the current work on uncertainty classification/quantification and will document common and emergent research themes to allow all to learn from each other and build a more connected but still diverse and ever growing community of scientists.Read an interview with the editors to find out more:https://eos.org/editors-vox/reducing-uncertainty-in-hazard-prediction

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