| 在美国电子健康信息记录（EHR）的普及在带给人们更加便捷的服务的同时加大人们对其无法及时监控病症变化等弊端的忧虑。IBM曾联合约翰霍普金斯
大学和加州大学打造了一款名为Spatio Temporal Epidemiological Modeler (STEM)来试图解决这一问题。
最近IBM宣布将在原有版本的基础上升级STEM以适应新的需要。STEM能够整合来自不同来源的数据和病理模型供研究者或者医生使用。新升级的系统将具有更快的速度以应对不断增长的疾病数据和模型。（生物谷Bioon.com） 详细英文报道： The rise of electronic health records (EHRs) is cutting the time it takes to spot changes in incidence of disease, but without context it is hard to see what is driving the shifts. A Big Data analytics platform from IBM ($IBM), Johns Hopkins University and the University of California is aiming to facilitate these insights. IBM and its partners built the open-source modeling platform--called Spatio Temporal Epidemiological Modeler (STEM)--to combine data from different sources. Early projects include looking at World Health Organization data on incidence of malaria alongside climate and temperature information. The Eclipse Foundation has made these capabilities freely available to researchers, and is now set to roll out STEM 2.0 later this month, MedCityNews reports. By opening up the ability to quickly crunch disease data, the collaborators hope to improve the speed and effectiveness of responses to outbreaks. "We have to be ready at the drop of a hat to parse through disparate data from global disease surveillance systems, conduct computationally intense research and transfer our knowledge to public health officials to help them visualize population health, detect outbreaks, develop new models, and evaluate the effectiveness of policies," University of California's Simone Bianco said. University of California is involved with a project to improve modeling of dengue fever, which, along with malaria, has been an initial area of focus for the data-centric approach. Having established the platform--which IBM is planning to provide in the cloud--the collaborators hope it sparks further projects. "One of the nice things about open-source projects like STEM is that now whoever wants to can download the model and start tweaking it, seeing if their own data or assumptions fundamentally change the results," Justin Lessler, of Johns Hopkins Bloomberg School of Public Health, said. |
