Le Fèvre C, Poty L, Noël G
Département universitaire de radiothérapie, centre Paul-Strauss, unicancer, 3, rue de la Porte-de-l'Hôpital, 67065 Strasbourg cedex, France.
Département informatique, centre Paul-Strauss, unicancer, 3, rue de la Porte-de-l'Hôpital, 67065 Strasbourg cedex, France.
Cancer Radiother. 2018 Feb;22(1):73-84. doi: 10.1016/j.canrad.2017.04.013. Epub 2017 Nov 14.
The many advances in data collection computing systems (data collection, database, storage), diagnostic and therapeutic possibilities are responsible for an increase and a diversification of available data. Big data offers the capacities, in the field of health, to accelerate the discoveries and to optimize the management of patients by combining a large volume of data and the creation of therapeutic models. In radiotherapy, the development of big data is attractive because data are very numerous et heterogeneous (demographics, radiomics, genomics, radiogenomics, etc.). The expectation would be to predict the effectiveness and tolerance of radiation therapy. With these new concepts, still at the preliminary stage, it is possible to create a personalized medicine which is always more secure and reliable.
数据收集计算系统（数据收集、数据库、存储）、诊断和治疗可能性方面的诸多进展，导致了可用数据的增加和多样化。大数据在健康领域具备通过整合大量数据及创建治疗模型来加速发现并优化患者管理的能力。在放射治疗中，大数据的发展颇具吸引力，因为数据数量众多且种类繁杂（人口统计学、放射组学、基因组学、放射基因组学等）。预期目标是预测放射治疗的有效性和耐受性。借助这些仍处于初步阶段的新概念，有可能打造出更加安全可靠的个性化医疗。
