EHR-RAGp: Retrieval-Augmented Prototype-Guided Foundation Model for Electronic Health Records
Electronic Health Records (EHR) contain rich longitudinal patient information and are widely used in predictive modeling applications. However, effectively leveraging historical data remains challenging due to long trajectories, heterogeneous events, temporal irregularity, and the varying relevance of past clinical context. Existing approaches often rely on fixed windows or uniform aggregation, which can obscure clinically important signals. In this work, we introduce EHR-RAGp, a retrieval-augme
Record details
Published: 12 May 2026
Source: arXiv
Category: Research
Topics: Healthcare
Retrieved: 14 July 2026
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ethics.ai (12 May 2026), “EHR-RAGp: Retrieval-Augmented Prototype-Guided Foundation Model for Electronic Health Records,” evidence record 4453, https://ethics.ai/record/4453 (originally published by arXiv).
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