论文标题
建模MRSA非殖民化：身体部位之间的相互作用与特定地点清除的影响
Modeling MRSA decolonization: Interactions between body sites and the impact of site-specific clearance
论文作者
论文摘要
MRSA定居是一个关键的公共卫生问题。已设计非殖民化协议用于清除MRSA。成功的非殖民化方案降低了疾病的发病率；但是，存在多种方案，包括针对多个身体部位的各种疗法，最佳方案尚不清楚。在这里，我们使用MRSA非殖民化的随机对照试验（RCT）中的数据制定了机器学习模型，该试验估计了身体部位之间的相互作用，量化了每种疗法对成功非殖民化的贡献，并可以预测治疗组合功效。这项工作显示了机器学习模型如何帮助设计和改善复杂的临床方案。
MRSA colonization is a critical public health concern. Decolonization protocols have been designed for the clearance of MRSA. Successful decolonization protocols reduce disease incidence; however, multiple protocols exist, comprising diverse therapies targeting multiple body sites, and the optimal protocol is unclear. Here, we formulate a machine learning model using data from a randomized controlled trial (RCT) of MRSA decolonization, which estimates interactions between body sites, quantifies the contribution of each therapy to successful decolonization, and enables predictions of the efficacy of therapy combinations. This work shows how a machine learning model can help design and improve complex clinical protocols.
