ArticleNPJ digital medicine2024
A scoping review of large language model based approaches for information extraction from radiology reports.
Article in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.
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Who cites it
51 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Large language models for simplifying radiology reports: a systematic review and meta-analysis of patient, public, and clinician evaluations.The Lancet. Digital health · 2026Pooled it
- Multidisciplinary attitudes towards LLM-structured oncologic CT reports: a prospective fixed-sequence questionnaire study.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- The consensus-based CINEX guideline for reporting clinical information extraction studies.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- SPELL: A scalable NLP method using regular expressions and large language models for clinical information extraction.Computer methods and programs in biomedicine · 2026Article
- Automated Identification of Complex Percutaneous Coronary Intervention from Cardiac Catheterization Reports using Large Language Models.medRxiv : the preprint server for health sciences · 2026Article
- Transparent, Reproducible Text-Based Phenotyping of Lumbar Intervertebral Disc Degeneration from 500 Consecutive MRI Reports, with a Pre-Specified Image Analysis Framework.Diagnostics (Basel, Switzerland) · 2026Article
- Multi-reader, multi-model benchmark of large language models for modified Outerbridge cartilage grading from knee MRI reports.Skeletal radiology · 2026Article
- Mapping the generative era: a bibliometric and specialty-focused analysis of large language models in healthcare.Visual computing for industry, biomedicine, and art · 2026Article
- Large Language Model Translation of BI-RADS Breast Imaging Reports into Arabic: A Blinded Expert Evaluation of Diagnostic Communication Safety.Diagnostics (Basel, Switzerland) · 2026Article
- Leveraging large language models for information extraction from free-text liver MRI reports and assessment of clinical utility: a multicenter study.Quantitative imaging in medicine and surgery · 2026Article
- Locally deployed context-aware chatbot outperforms generic large language models for guideline-concordant pediatric imaging recommendations.Pediatric radiology · 2026Article
- Large language models enable prognostic stratification of cancer patients using real-world clinical notes.PLOS digital health · 2026Article
- Evaluation of Large Language Models for Structured Data Extraction From Interstitial Lung Disease Clinical Notes: Comparative Study.Journal of medical Internet research · 2026Article
- Voice-controlled super-resolution ultrasound imaging and reporting powered by multimodal large language models.NPJ digital medicine · 2026Article
- Intelligent documentation in medical education: can AI replace manual case logging?JAMIA open · 2026Article
- Implementing a Resource-Light and Low-Code Large Language Model System for Information Extraction from Mammography Reports: A Pilot Study.Journal of imaging informatics in medicine · 2026Article
- Who labels best? Radiologists, rules, or large language models for CT reports on pulmonary embolism.European radiology experimental · 2026Article
- Automated RECIST tumor response classification through prompt-guided large language models.Scientific reports · 2026Article
- BI-RADS-compliant structured mammography reporting using locally deployed large language models under privacy constraints.European radiology · 2026Article
- AI application in radiology beyond imaging: What is the role of text-based large language models?European radiology · 2026Article
Corrections and comments
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Authors and funding
3 authors.
Funding
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Abstract
Radiological imaging is a globally prevalent diagnostic method, yet the free text contained in radiology reports is not frequently used for secondary purposes. Natural Language Processing can provide structured data retrieved from these reports. This paper provides a summary of the current state of research on Large Language Model (LLM) based approaches for information extraction (IE) from radiology reports. We conduct a scoping review that follows the PRISMA-ScR guideline. Queries of five databases were conducted on August 1st 2023. Among the 34 studies that met inclusion criteria, only pre-transformer and encoder-based models are described. External validation shows a general performance decrease, although LLMs might improve generalizability of IE approaches. Reports related to CT and MRI examinations, as well as thoracic reports, prevail. Most common challenges reported are missing validation on external data and augmentation of the described methods. Different reporting granularities affect the comparability and transparency of approaches.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.