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                <term xml:lang="en">Clinical data warehouse</term>
                <term xml:lang="en">Deep Learning</term>
                <term xml:lang="en">Big Data</term>
                <term xml:lang="en">Sarcope- nia</term>
                <term xml:lang="en">Artificial Intelligence</term>
                <term xml:lang="en">Nutrition</term>
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              <p>Big Data and Deep Learning approaches offer new opportunities for medical data analysis. With these technologies, PREDIMED, the clinical data warehouse of Grenoble Alps University Hospital, sets up first clinical studies on retrospective data. In particular, ODIASP study, aims to develop and evaluate deep learning-based tools for automatic sarcopenia diagnosis, while using data collected via PREDIMED, in particular, medical images. Here we describe a methodology of data preparation for a clinical study via PREDIMED.</p>
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