How the mass media report social statistics: A case study concerning research on end-of-life decisions

This is the post-print version of the final paper published in Social Science & Medicine. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.The issue of whether it is right to be concerned about the accuracy with which mass media report social scientific research is explored through a detailed case study of media reporting of two surveys of UK doctors' end-of-life decision-making. Data include press releases, emails and field notes taken during periods of media interest supplemented by a collection of print and broadcast media reports. The case study contributes to existing knowledge about the ways in which mass media establish, exaggerate and otherwise distort the meaning of statistical findings. Journalists ignored findings that did not fit into existing media interest in the 'assisted dying' story and were subject to pressure from interest groups concerned to promote their own interpretations and viewpoints. Rogue statistics mutated as they were set loose from their original research report context and were 'laundered' as they passed from one media report to another. Yet media accounts of the research, fuelling an already heated public debate about ethical issues in end-of-life care, arguably acted as a conduit for introducing new considerations into this debate, such as the role played by sedation at the end of life, the extent to which euthanasia is practiced outside the law, and the extent of medical opposition to the legalisation of assisted dying. The expectation that accuracy and comprehensiveness should be the sole criteria for judging journalists' reports is, finally, considered to be unrealistic and it is argued that social scientists need to understand and adapted to the conditions under which mass media reporting operates if they are to succeed in introducing the findings of social research into public debates.The Nuffield Foundation, the National Council for Palliative Care, Age Concern, the Motor Neurone Disease Association, the Multiple Sclerosis Society, Help the Hospices, Macmillan Cancer Support, and Sue Ryder Care

A Survey on Deep Learning in Medical Image Analysis

Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year. We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks and provide concise overviews of studies per application area. Open challenges and directions for future research are discussed.Comment: Revised survey includes expanded discussion section and reworked introductory section on common deep architectures. Added missed papers from before Feb 1st 201