Lagani Vincenzo, Chiarugi Franco, Manousos Dimitris, Verma Vivek, Fursse Joanna, Marias Kostas, Tsamardinos Ioannis
Institute of Computer Science, Foundation for Research and Technology-Hellas, Heraklion, Greece.
Institute of Computer Science, Foundation for Research and Technology-Hellas, Heraklion, Greece.
J Diabetes Complications. 2015 Jul;29(5):691-8. doi: 10.1016/j.jdiacomp.2015.03.011. Epub 2015 Mar 25.
We present a computerized system for the assessment of the long-term risk of developing diabetes-related complications.
The core of the system consists of a set of predictive models, developed through a data-mining/machine-learning approach, which are able to evaluate individual patient profiles and provide personalized risk assessments. Missing data is a common issue in (electronic) patient records, thus the models are paired with a module for the intelligent management of missing information.
The system has been deployed and made publicly available as Web service, and it has been fully integrated within the diabetes-management platform developed by the European project REACTION. Preliminary usability tests showed that the clinicians judged the models useful for risk assessment and for communicating the risk to the patient. Furthermore, the system performs as well as the United Kingdom Prospective Diabetes Study (UKPDS) Risk Engine when both systems are tested on an independent cohort of UK diabetes patients.
Our work provides a working example of risk-stratification tool that is (a) specific for diabetes patients, (b) able to handle several different diabetes related complications, (c) performing as well as the widely known UKPDS Risk Engine on an external validation cohort.
我们展示了一个用于评估糖尿病相关并发症长期风险的计算机化系统。
该系统的核心由一组通过数据挖掘/机器学习方法开发的预测模型组成，这些模型能够评估个体患者概况并提供个性化风险评估。缺失数据是（电子）患者记录中的常见问题，因此这些模型与一个用于智能管理缺失信息的模块相结合。
该系统已作为网络服务进行部署并公开可用，并且已完全集成到欧洲项目REACTION开发的糖尿病管理平台中。初步可用性测试表明，临床医生认为这些模型对于风险评估以及向患者传达风险很有用。此外，当在一组独立的英国糖尿病患者中对这两个系统进行测试时，该系统的表现与英国前瞻性糖尿病研究（UKPDS）风险引擎相当。
我们的工作提供了一个风险分层工具的实际示例，该工具（a）针对糖尿病患者，（b）能够处理几种不同的糖尿病相关并发症，（c）在外部验证队列中的表现与广为人知的UKPDS风险引擎相当。
