NCBI PubMed Central
open access
Data Extraction From Oncology Imaging Reports by Large Language Models: A Comparative Accuracy Study.
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
- Fine-tuned lightweight language models for structured extraction of liver cancer imaging free-text report: a comparative analysis with existing large language models.#148246
- The consensus-based CINEX guideline for reporting clinical information extraction studies#983892
- De-identification of clinical data: A systematic review of free text, image and tabular data approaches.#9548
- Enhanced lung cancer detection using BiLSTM attention and transformer models on clinical text data.#653516
- Large-Language Models for data extraction from written kidney biopsy reports#387695
Record · ID 449838
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