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Stefano Canali
Politecnico di Milano
  1. Evaluating evidential pluralism in epidemiology: mechanistic evidence in exposome research.Stefano Canali - 2019 - History and Philosophy of the Life Sciences 41 (1):4.
    In current philosophical discussions on evidence in the medical sciences, epidemiology has been used to exemplify a specific version of evidential pluralism. According to this view, known as the Russo–Williamson Thesis, evidence of both difference-making and mechanisms is produced to make causal claims in the health sciences. In this paper, I present an analysis of data and evidence in epidemiological practice, with a special focus on research on the exposome, and I cast doubt on the extent to which evidential pluralism (...)
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  2. Open science, data sharing and solidarity: who benefits?Ciara Staunton, Carlos Andrés Barragán, Stefano Canali, Calvin Ho, Sabina Leonelli, Matthew Mayernik, Barbara Prainsack & Ambroise Wonkham - 2021 - History and Philosophy of the Life Sciences 43 (4):1-8.
    Research, innovation, and progress in the life sciences are increasingly contingent on access to large quantities of data. This is one of the key premises behind the “open science” movement and the global calls for fostering the sharing of personal data, datasets, and research results. This paper reports on the outcomes of discussions by the panel “Open science, data sharing and solidarity: who benefits?” held at the 2021 Biennial conference of the International Society for the History, Philosophy, and Social Studies (...)
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  3. Towards a Contextual Approach to Data Quality.Stefano Canali - 2020 - Data 4 (5):90.
    In this commentary, I propose a framework for thinking about data quality in the context of scientific research. I start by analyzing conceptualizations of quality as a property of information, evidence and data and reviewing research in the philosophy of information, the philosophy of science and the philosophy of biomedicine. I identify a push for purpose dependency as one of the main results of this review. On this basis, I present a contextual approach to data quality in scientific research, whereby (...)
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  4. Reframing the environment in data-intensive health sciences.Stefano Canali & Sabina Leonelli - 2022 - Studies in History and Philosophy of Science Part A 93:203-214.
    In this paper, we analyse the relation between the use of environmental data in contemporary health sciences and related conceptualisations and operationalisations of the notion of environment. We consider three case studies that exemplify a different selection of environmental data and mode of data integration in data-intensive epidemiology. We argue that the diversification of data sources, their increase in scale and scope, and the application of novel analytic tools have brought about three significant conceptual shifts. First, we discuss the EXPOsOMICS (...)
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  5. Challenges and recommendations for wearable devices in digital health: Data quality, interoperability, health equity, fairness.Stefano Canali, Viola Schiaffonati & Andrea Aliverti - 2022 - PLOS Digital Health 1 (10):e0000104.
    Wearable devices are increasingly present in the health context, as tools for biomedical research and clinical care. In this context, wearables are considered key tools for a more digital, personalised, preventive medicine. At the same time, wearables have also been associated with issues and risks, such as those connected to privacy and data sharing. Yet, discussions in the literature have mostly focused on either technical or ethical considerations, framing these as largely separate areas of discussion, and the contribution of wearables (...)
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  6. Big Data, epistemology and causality: Knowledge in and knowledge out in EXPOsOMICS.Stefano Canali - 2016 - Big Data and Society 3 (2).
    Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show how causal knowledge is necessary for (...)
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  7. Wearable Technologies for Healthy Ageing: Prospects, Challenges, and Ethical Considerations.Stefano Canali, Agara Ferretti, Viola Schiaffonati & Alessandro Blasimme - 2024 - Journal of Frailty and Aging 2024:1-8.
    Digital technologies hold promise to modernize healthcare. Such opportunity should be leveraged also to address the needs of rapidly ageing populations. Against this backdrop, this paper examines the use of wearable devices for promoting healthy ageing. Previous work has assessed the prospects of digital technologies for health promotion and disease prevention in older adults. However, to our knowledge, ours is one of the first attempts to specifically address the use of wearables for healthy ageing, and to offer ethical insights for (...)
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  8. A pragmatic approach to scientific change: transfer, alignment, influence.Stefano Canali - 2022 - European Journal for Philosophy of Science 12 (3):1-25.
    I propose an approach that expands philosophical views of scientific change, on the basis of an analysis of contemporary biomedical research and recent developments in the philosophy of scientific change. Focusing on the establishment of the exposome in epidemiology as a case study and the role of data as a context for contrasting views on change, I discuss change at conceptual, methodological, material, and social levels of biomedical epistemology. Available models of change provide key resources to discuss this type of (...)
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  9. The paradox of the artificial intelligence system development process: the use case of corporate wellness programs using smart wearables.Alessandra Angelucci, Ziyue Li, Niya Stoimenova & Stefano Canali - forthcoming - AI and Society:1-11.
    Artificial intelligence systems have been widely applied to various contexts, including high-stake decision processes in healthcare, banking, and judicial systems. Some developed AI models fail to offer a fair output for specific minority groups, sparking comprehensive discussions about AI fairness. We argue that the development of AI systems is marked by a central paradox: the less participation one stakeholder has within the AI system’s life cycle, the more influence they have over the way the system will function. This means that (...)
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  10.  80
    Introduction: The philosophy, ethics, and politics of epidemiology today.Stefano Canali & Corrado Piroddi - 2021 - Mefisto Rivista di Medicina, Filosofia, Storia 5 (1).
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