PRODIGE：前列腺癌个体化医学挑战中的预测模型。
PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE.
机构信息
Radiation Oncology Area, Gemelli-ART, Catholic University of the Sacred Heart, Rome, Italy.
Department of Radiation Oncology (MAASTRO), GROW - School for Oncology & Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands.
出版信息
Future Oncol. 2017 Oct;13(24):2171-2181. doi: 10.2217/fon-2017-0142. Epub 2017 Jul 31.
AIM
Identifying the best care for a patient can be extremely challenging. To support the creation of multifactorial Decision Support Systems (DSSs), we propose an Umbrella Protocol, focusing on prostate cancer.
MATERIALS & METHODS: The PRODIGE project consisted of a workflow for standardizing data, and procedures, to create a consistent dataset useful to elaborate DSSs. Techniques from classical statistics and machine learning will be adopted. The general protocol accepted by our Ethical Committee can be downloaded from cancerdata.org .
RESULTS
A standardized knowledge sharing process has been implemented by using a semi-formal ontology for the representation of relevant clinical variables.
CONCLUSION
The development of DSSs, based on standardized knowledge, could be a tool to achieve a personalized decision-making.
目的
为患者提供最佳护理可能极具挑战性。为了支持多因素决策支持系统 (DSS) 的创建，我们提出了一个伞式协议，重点关注前列腺癌。
材料与方法
PRODIGE 项目包括一个用于标准化数据和程序的工作流程，以创建一个有用的一致数据集来开发 DSS。将采用来自经典统计学和机器学习的技术。我们的伦理委员会接受的一般协议可以从 cancerdata.org 下载。
结果
通过使用半形式本体来表示相关临床变量，实现了标准化知识共享过程。
结论
基于标准化知识的 DSS 的开发可能是实现个性化决策的工具。
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