PubMed
open access
CC BY-NC 4.0
Benchmarking large language models for de-identification of electronic health record notes.
benchmarkingconfidentialityelectronic-health-recordshumanslarge-language-modelsnatural-language-processing
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
- Benchmarking large language models for de-identification of electronic health record notes.#409320
- Scalable medication extraction and discontinuation identification from electronic health records using large language models.#145928
- Automatic de-identification of textual documents in the electronic health record: a review of recent research#976501
- Natural language processing application to identify covert administration of medicines: development and pilot audit.#161965
- A Living Benchmark for Information Retrieval from Electronic Health Records#1078276
Record · ID 396737
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