TreeText-CTS builds source-traceable tree-path evidence from multi-scale EHR windows via frozen XGBoost, selects subsets, and uses an LM encoder to reach top AUPRC among text-based interfaces on mortality and sepsis tasks while staying competitive with numerical models.
TimeCAP: Learning to contextualize, augment, and predict time series events with large language model agents
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TreeText-CTS: Compact, Source-Traceable Tree-Path Evidence for Irregular Clinical Time-Series Prediction
TreeText-CTS builds source-traceable tree-path evidence from multi-scale EHR windows via frozen XGBoost, selects subsets, and uses an LM encoder to reach top AUPRC among text-based interfaces on mortality and sepsis tasks while staying competitive with numerical models.