Utilisations actuelles et impact du Big Data en psychiatrie

Abstract : The success of Big Data analytics and machine learning in business and the technology industry is driving an enthusiastic push by public authorities, the private sector and biomedical research for a massive deployment of Big Data in health. The promise of transforming healthcare through data-driven individual predictions is central to the discourse surrounding precision medicine, also described as predictive, preventive, personalized and participative. The current work begins with a defnition of Big Data, based on a description of its techniques and architecture, as well as its political and cultural contexts, with a focus on healthcare. This recontextualization allows us to then evaluate the impact of Big Data on clinical practice in psychiatry. First, through a selective review of the medical and scientifc literature, examples of uses of Big Data in psychiatry are identifed. They pertain to the classifcation, prediction and monitoring of psychiatric disorders, as well as to scientifc discovery in psychiatry. A critical analysis of their statistical methodology reveals that the use of Big Data in psychiatry is still at a preliminary stage, quite far from afecting real change in clinical practice, and that the methodological complexity of psychiatric research will not be solved anytime soon. Next, through a number of theoretical critical perspectives, we show that Big Data in psychiatry raises questions related to ethics, epistemology and subjectivity/personhood. A clinical refection on these issues is proposed here, with a call for further clinical readings of the questions raised by Big Data in psychiatry.
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Aisha Belhadi. Utilisations actuelles et impact du Big Data en psychiatrie. Médecine humaine et pathologie. 2018. ⟨dumas-02115073⟩

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