论文标题
在流行病学监测和准备性之间的差距上
On the Gap between Epidemiological Surveillance and Preparedness
论文作者
论文摘要
当代流行病学监测（ES）在很大程度上依赖于数据分析。这些分析是Pandemics准备网络的关键输入。但是，此输入并未集成为适合决策者或准备专家的形式。需要使用计算智能（CI）工具的决策支持系统（DSS）来弥合证据流行病学模型与专家小组决策之间的差距。我们认为，这样的DSS将是一个认知动态系统，使CI和人类专家能够共同努力。此类DSS的核心必须基于机器推理技术，例如概率推断，并且应能够估算决策中的风险，可靠性和偏见。
Contemporary Epidemiological Surveillance (ES) relies heavily on data analytics. These analytics are critical input for pandemics preparedness networks; however, this input is not integrated into a form suitable for decision makers or experts in preparedness. A decision support system (DSS) with Computational Intelligence (CI) tools is required to bridge the gap between epidemiological model of evidence and expert group decision. We argue that such DSS shall be a cognitive dynamic system enabling the CI and human expert to work together. The core of such DSS must be based on machine reasoning techniques such as probabilistic inference, and shall be capable of estimating risks, reliability and biases in decision making.
