This article explores the critical role of statistical analysis in precision medicine. It discusses how personalized healthcare is enhanced by statistical methods that interpret complex, multidimensional datasets, focusing on predictive modeling, machine learning algorithms, and data visualization techniques. The paper addresses challenges in data integration and interpretation, particularly with diverse data sources like electronic health records (EHRs) and genomic data. It also delves into ethical considerations such as patient privacy and data security. In addition, the paper highlights the evolution of statistical analysis in medicine, core statistical methodologies in precision medicine, and future directions in the field, emphasizing the integration of artificial intelligence (AI) and machine learning (ML).

翻译：本文探讨了统计分析在精准医学中的关键作用。文章阐述了统计方法如何通过解读复杂的多维数据集来增强个性化医疗，重点聚焦预测建模、机器学习算法及数据可视化技术。论文分析了数据整合与解读中的挑战，特别是在电子健康记录（EHRs）和基因组数据等多源异构数据源的应用中。研究还深入探讨了患者隐私与数据安全等伦理问题。此外，论文着重强调了精准医学中统计分析的演进历程、核心统计方法论及该领域未来发展方向，特别指出人工智能（AI）与机器学习（ML）的融合趋势。