FlatASCEND generates conditional clinical event sequences that partially recover known mechanistic drug associations from observational data but fail to maintain them under direct preference optimization and show weaker performance on longer outpatient timelines.
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FlatASCEND: Autoregressive Clinical Sequence Generation with Continuous Time Prediction and Association-Based Pharmacological Testing
FlatASCEND generates conditional clinical event sequences that partially recover known mechanistic drug associations from observational data but fail to maintain them under direct preference optimization and show weaker performance on longer outpatient timelines.