Precision medicine is an increasingly important area of research. Due to the heterogeneity individual characteristics, patients may respond differently treatments. One most goals for precision develop individualized treatment rules (ITRs) involving patients’ characteristics directly. As interesting topic in clinical research, many statistical methods have been developed recent years find optima...

Data-driven individualized decision making has recently received increasing research interest. However, most existing methods rely on the assumption of no unmeasured confounding, which cannot be ensured in practice especially observational studies. Motivated by proposed proximal causal inference, we develop several learning to estimate optimal treatment regimes (ITRs) presence confounding. Expl...