Precision medicine seeks to maximize the quality of healthcare by individualizing the healthcare process to the uniquely evolving health status of each patient. This endeavor spans a broad range of scientific areas including drug discovery, genetics/genomics, health communication, and causal inference all in support of evidence-based, i.e., data-driven, decision making. Precision medicine is formalized as a treatment regime which comprises a sequence of decision rules, one per decision point, which map up-to-date patient information to a recommended action. The potential actions could be the selection of which drug to use, the selection of dose, timing of administration, specific diet or exercise recommendation, or other aspects of treatment or care. Statistics research in precision medicine is broadly focused on methodological development for estimation of and inference for treatment regimes which maximize some cumulative clinical outcome. In this review, we provide an overview of this vibrant area of research and present important and emerging challenges.

中文翻译：

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 精准医学。


精准医疗旨在通过根据每位患者独特发展的健康状况制定个性化医疗流程，最大限度地提高医疗质量。这项努力涵盖了广泛的科学领域，包括药物发现、遗传学/基因组学、健康传播和因果推理，所有这些都支持基于证据的决策，即数据驱动的决策。精准医学被正式化为一种治疗方案，包括一系列决策规则，每个决策点一个，将最新的患者信息映射到推荐的行动。潜在的行动可能是选择使用哪种药物、选择剂量、给药时间、具体饮食或运动建议，或治疗或护理的其他方面。精准医学的统计研究广泛关注用于估计和推断治疗方案的方法学开发，以最大化一些累积的临床结果。在这篇综述中，我们概述了这一充满活力的研究领域，并提出了重要的和正在出现的挑战。