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ODIASP: Clinically Contextualized Image Analysis Using the PREDIMED Clinical Data Warehouse, Towards a Better
Katia Charrière1, Pierre-Ephrem Madiot2, Svetlana Artemova1,3
1Clinical Investigation Center-Technological Innovation, Univ. Grenoble Alpes, INSERM CIC1406, CHU Grenoble Alpes, F-38000, Grenoble, France.
Abstract:
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.
