论文标题
网络荟萃分析：统计物理学观点
Network Meta-Analysis: A Statistical Physics Perspective
论文作者
论文摘要
网络荟萃分析（NMA）是一种在医学统计数据中用于结合多个医学试验的证据的技术。 NMA在治疗方案网络和连接治疗的试验上定义了推论和信息处理问题。我们认为，统计物理学可以为该领域提供有用的想法和工具，包括复杂网络，随机建模和仿真技术的理论。缺乏独特的来源，可以使物理学家有效地了解NMA是一个障碍。在本文中，我们旨在介绍“ NMA问题”，并以统计物理学家访问的语言连贯地使用它的现有方法。我们还总结了统计物理和NMA之间的现有联系点，并描述了我们关于物理如何在将来对NMA产生影响的想法。本文的总体目标是吸引物理学家进入这个有趣，及时和有价值的研究领域。
Network meta-analysis (NMA) is a technique used in medical statistics to combine evidence from multiple medical trials. NMA defines an inference and information processing problem on a network of treatment options and trials connecting the treatments. We believe that statistical physics can offer useful ideas and tools for this area, including from the theory of complex networks, stochastic modelling and simulation techniques. The lack of a unique source that would allow physicists to learn about NMA effectively is a barrier to this. In this article we aim to present the `NMA problem' and existing approaches to it coherently and in a language accessible to statistical physicists. We also summarise existing points of contact between statistical physics and NMA, and describe our ideas of how physics might make a difference for NMA in the future. The overall goal of the article is to attract physicists to this interesting, timely and worthwhile field of research.
