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Updated: Jun 25, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Lexomics, or why to extract relevant information from radiology reports through LLMs
Teodoro Martín-Noguerol1, Pilar López-Úbeda2, Carolina Díaz-Angulo3
1MRI Unit, Radiology Department, HT Medica, Carmelo Torres 2, 23007, Jaén, Spain. t.martin.f@htime.org.
Large language models (LLMs) applied to radiology reports, a field called lexomics, extract valuable data for better clinical decisions. This AI approach enhances report analysis and integration into electronic health records.
Area of Science:
- Artificial intelligence in medical imaging
- Natural language processing in healthcare
- Radiology informatics
Background:
- Radiology reports contain rich textual data crucial for patient management.
- Current methods may not fully leverage the information within unstructured radiology reports.
- Lexomics, analogous to radiomics, aims to extract deeper insights from text.
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