论文标题
预测Covid-19期间的特殊护理：一种机器学习方法
Predicting special care during the COVID-19 pandemic: A machine learning approach
论文作者
论文摘要
与以往任何时候相比，Covid-19都对世界各地的卫生系统施加压力，尤其是在巴西。在这项研究中，我们提出了一种基于统计和机器学习的分析方法，该方法使用来自患者的实验室检查数据来预测患者是否需要特殊护理（定期或特殊护理单位住院）。我们还预测患者将在这种护理中留下的天数。开发的两步过程使用贝叶斯优化来选择几个候选者中的最佳模型，这使我们进入了第一个目标的ROC曲线性能下在ROC曲线性能下实现0.94区域的最终模型和第二个目标的1.87根平方平方误差（这是平均基线的77％提高），从而使我们的模型可用于所有人的决策系统，以适应所有人的型号。分析方法可用于其他疾病，可以帮助计划医院的能力。
More than ever COVID-19 is putting pressure on health systems all around the world, especially in Brazil. In this study we propose an analytical approach based on statistics and machine learning that uses lab exam data coming from patients to predict whether patients are going to require special care (hospitalisation in regular or special-care units). We also predict the number of days the patients will stay under such care. The two-step procedure developed uses Bayesian Optimisation to select the best model among several candidates leads us to final models that achieve 0.94 area under ROC curve performance for the first target and 1.87 root mean squared error for the second target (which is a 77% improvement over the mean baseline), making our model ready to be deployed as a decision system that could be available for everyone interested. The analytical approach can be used in other diseases and can help the planning hospital capacity.
