Clinical Investigation Center-Technological Innovation, Univ. Grenoble Alpes, INSERM CIC1406, CHU Grenoble Alpes, F-38000, Grenoble, France.
Digital Services Management, CHU Grenoble Alpes, F-38000, Grenoble, France.
Stud Health Technol Inform. 2022 Jun 6;290:1068-1069. doi: 10.3233/SHTI220271.
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.
大数据和深度学习方法为医学数据分析带来了新的机遇。利用这些技术,格勒诺布尔阿尔卑斯大学医院的临床数据仓库 PREDIMED 正在对回顾性数据开展首批临床研究。特别是,ODIASP 研究旨在开发和评估基于深度学习的自动肌少症诊断工具,并利用 PREDIMED 收集的数据,特别是医学图像。本文介绍了一种通过 PREDIMED 进行临床研究的数据准备方法。