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利用GWAS汇总数据推断非线性因果效应AI 解读

Large-scale genome-wide association studies (GWAS) have offered an exciting opportunity to discover putative causal genes or risk factors associated with diseases by using SNPs as instrumental variables (IVs). However, conventional approaches assume linear causal relations partly for simplicity and partly for the availability of GWAS summary data. In this work, we propose a novel model {for transcriptome-wide association studies (TWAS)} to incorporate nonlinear relationships…

具有双层单调性的多阶段推荐系统AI 解读

A recommender system learns to predict the user-specific preference or intention over many items simultaneously for all users, making personalized recommendations based on a relatively small number of observations. One central issue is how to leverage three-way interactions, referred to as user-item-stage dependencies on a monotonic chain of events, to enhance the prediction accuracy. A monotonic chain of events occurs, for instance, in an article sharing dataset, where a…