Stabilized Neural Prediction of Potential Outcomes in Continuous Time
Stabilized Neural Prediction of Potential Outcomes in Continuous Time
Patient trajectories from electronic health records are widely used to predict potential outcomes of treatments over time, which then allows to personalize care. Yet, existing neural methods for this purpose have a key limitation: while some adjust for time-varying confounding, these methods assume that the time series are recorded in …