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  1. Digital epidemiology, deep phenotyping and the enduring fantasy of pathological omniscience.Lukas Engelmann - 2022 - Big Data and Society 9 (1).
    Epidemiology is a field torn between practices of surveillance and methods of analysis. Since the onset of COVID-19, epidemiological expertise has been mostly identified with the first, as dashboards of case and mortality rates took centre stage. However, since its establishment as an academic field in the early 20th century, epidemiology’s methods have always impacted on how diseases are classified, how knowledge is collected, and what kind of knowledge was considered worth keeping and analysing. Recent advances in digital epidemiology, this (...)
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  • Why Personal Dreams Matter: How professionals affectively engage with the promises surrounding data-driven healthcare in Europe.Antoinette de Bont, Anne Marie Weggelaar-Jansen, Johanna Kostenzer, Rik Wehrens & Marthe Stevens - 2022 - Big Data and Society 9 (1).
    Recent buzzes around big data, data science and artificial intelligence portray a data-driven future for healthcare. As a response, Europe's key players have stimulated the use of big data technologies to make healthcare more efficient and effective. Critical Data Studies and Science and Technology Studies have developed many concepts to reflect on such overly positive narratives and conduct critical policy evaluations. In this study, we argue that there is also much to be learned from studying how professionals in the healthcare (...)
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  • The cancer multiple: Producing and translating genomic big data into oncology care.Peter A. Chow-White & Tiên-Dung Hà - 2021 - Big Data and Society 8 (1).
    This article provides an ethnographic account of how Big Data biology is produced, interpreted, debated, and translated in a Big Data-driven cancer clinical trial, entitled “Personalized OncoGenomics,” in Vancouver, Canada. We delve into epistemological differences between clinical judgment, pathological assessment, and bioinformatic analysis of cancer. To unpack these epistemological differences, we analyze a set of gazes required to produce Big Data biology in cancer care: clinical gaze, molecular gaze, and informational gaze. We are concerned with the interactions of these bodily (...)
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  • Institutions, infrastructures, and data friction – Reforming secondary use of health data in Finland.Ville Aula - 2019 - Big Data and Society 6 (2).
    New data-driven ideas of healthcare have increased pressures to reform existing data infrastructures. This article explores the role of data governing institutions during a reform of both secondary health data infrastructure and related legislation in Finland. The analysis elaborates on recent conceptual work on data journeys and data frictions, connecting them to institutional and regulatory issues. The study employs an interpretative approach, using interview and document data. The results show the stark contrast between the goals of open and Big Data (...)
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