Advanced Bayesian kernel machine regression for large-scale exposome studies: Making the impossible possible

作者：Yi Guo, Huixun Jia, Ziwei Peng, Xinming Xu, Zhicheng Zhang, Keyu Pan, Yuqin Zhou, Haidong Kan, Zhenyu Wu, Cong Liu · 发表于：The Innovation · 年份：2026 · DOI：10.1016/j.xinn.2025.101248 · 被引用次数：2 · 研究领域：Health, Environment, Cognitive Aging、Epigenetics and DNA Methylation、Gaussian Processes and Bayesian Inference

> 0.97 across scenarios with varying sample sizes and numbers of exposures. Furthermore, A-BKMR introduces novel quantitative metrics for effect estimates and interaction analyses, substantially enhancing interpretability. These advancements establish A-BKMR as an excellent statistical framework for future large-scale exposome studies.