A pipeline of temporal causal normalizing flows and LLM-based evolutionary imputation estimates treatment effects from incomplete EHRs, recovering a weight-loss difference consistent with randomized evidence in a diabetes study.
Systolic blood pressure (SBP) at timetis: SBP(t) = 70 SBP(t−1) SBP0 + 0.5 age(t) + 0.15 TC(t) + 10 smoker +ε, ε∼ N(0,400), clipped to[80,200]
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Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation
A pipeline of temporal causal normalizing flows and LLM-based evolutionary imputation estimates treatment effects from incomplete EHRs, recovering a weight-loss difference consistent with randomized evidence in a diabetes study.