arXiv (All)
open access
Clinical Note Bloat Reduction for Efficient LLM Use
Background: Clinical notes contain extensive duplicated text from templates, copy-paste, and auto-populated fields ("note bloat"), diluting clinical signal, limiting longitudinal context, and increasing large language model (LLM) costs. Methods: TRACE removes note bloat using note-level EHR metada
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Reducing risk factors for heart disease by telephone follow-up after hospitalization#488755
- Balancing clinical relevance, legal boundaries, and technological solutions: a case-based analysis of secondary use of electronic health records in Sweden.#826
- Search for Childhood Cancer Survivorship and Guideline Adherence#978653
- Validating exacerbations of asthma in electronic health records: a systematic review.#236002
- Tobacco Cessation Texting Intervention for People Living With HIV Who Smoke in Vietnam#1060736
Record · ID 1156331
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive