ODIASP: Clinically Contextualized Image Analysis Using the PREDIMED Clinical Data Warehouse, Towards a Better Diagnosis of Sarcopenia

Autor: Katia, Charrière, Pierre-Ephrem, Madiot, Svetlana, Artemova, Pungponhavoan, Tep, Christian, Lenne, Brigitte, Cohard, Alban, Caporossi, Isabelle, Boudry, Juliette, Meyzenc, Gilbert, Ferretti, Ivan, Bricault, Joris, Giai, Jean-Luc, Bosson, Eric, Fontaine, Cécile, Bétry, Alexandre, Moreau-Gaudry
Rok vydání: 2022
Předmět:
Zdroj: Studies in health technology and informatics. 290
ISSN: 1879-8365
Popis: 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.
Databáze: OpenAIRE