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基于人工智能算法和健康数据的 SINFONIA 项目存储库。

The SINFONIA project repository for AI-based algorithms and health data.

机构信息

Galicia Supercomputing Center (CESGA), Santiago de Compostela, Galicia, Spain.

出版信息

Front Public Health. 2024 Oct 23;12:1448988. doi: 10.3389/fpubh.2024.1448988. eCollection 2024.

DOI:10.3389/fpubh.2024.1448988
PMID:39507665
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11539176/
Abstract

The SINFONIA project's main objective is to develop novel methodologies and tools that will provide a comprehensive risk appraisal for detrimental effects of radiation exposure on patients, workers, caretakers, and comforters, the public, and the environment during the management of patients suspected or diagnosed with lymphoma, brain tumors, and breast cancers. The project plan defines a series of key objectives to be achieved on the way to the main objective. One of these objectives is to develop and operate a repository to collect, pool, and share data from imaging and non-imaging examinations and radiation therapy sessions, histological results, and demographic information related to individual patients with lymphoma, brain tumors, and breast cancers. This paper presents the final version of that repository, a cloud-based platform for imaging and non-imaging data. It results from the implementation and integration of several software tools and programming frameworks under an evolutive architecture according to the project partners' needs and the constraints of the General Data Protection Regulation. It provides, among other services, data uploading and downloading, data sharing, file decompression, data searching, DICOM previsualization, and an infrastructure for submitting and running Artificial Intelligence models.

摘要

SINFONIA 项目的主要目标是开发新的方法和工具，为疑似或诊断患有淋巴瘤、脑肿瘤和乳腺癌的患者在管理过程中，对辐射暴露对患者、工作人员、护理人员、公众和环境的有害影响进行全面风险评估。项目计划定义了一系列在实现主要目标的过程中需要实现的关键目标。其中一个目标是开发和运营一个存储库，用于收集、汇集和共享与淋巴瘤、脑肿瘤和乳腺癌个体患者相关的成像和非成像检查以及放射治疗、组织学结果和人口统计学信息。本文介绍了该存储库的最终版本，这是一个基于云的成像和非成像数据平台。它是根据项目合作伙伴的需求和通用数据保护条例的限制，通过实施和集成几个软件工具和编程框架而构建的，具有进化式架构。它提供了数据上传和下载、数据共享、文件解压缩、数据搜索、DICOM 预览以及提交和运行人工智能模型的基础设施等服务。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e764/11539176/366509d3cda1/fpubh-12-1448988-g014.jpg
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