ArticleArchives of orthopaedic and trauma surgery2024
Simplifying radiologic reports with natural language processing: a novel approach using ChatGPT in enhancing patient understanding of MRI results.
Article in Archives of orthopaedic and trauma surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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The trial behind it
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Who cites it
25 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
- Assessing the clinical applicability of large language models for microwave ablation guidance.European journal of radiology open · 2026Article
- Simplifying radiology reports with large language models: privacy-compliant open- versus closed-weight models.European radiology · 2026Article
- Applications, Challenges, and Future Directions of Large Language Models in Health Care Communication: Scoping Review.Journal of medical Internet research · 2026Article
- Exploring Radiologists' Use of AI Chatbots for Assistance in Image Interpretation: Patterns of Use and Trust Evaluation.Journal of imaging informatics in medicine · 2026Article
- Psychological Impact of AI-Simplified Brain MRI Reports: A Randomized Trial of Patient Understanding, Anxiety, and Health Literacy.Journal of clinical medicine · 2026Article
- Patient-friendly simplification and translation of neuroradiology impressions using artificial intelligence.Scientific reports · 2026Article
- ChatGPT, Claude Sonnet, and Grok Display Similarly Low Rates of Accuracy in Identifying Image-Based Orthopaedic Sports Pathologies.Arthroscopy, sports medicine, and rehabilitation · 2026Article
- Assessing the ability of large language models to simplify lumbar spine imaging reports into patient-facing text: a pilot study of GPT-4.Skeletal radiology · 2026Article
- Improving the readability of trauma patient education materials: a ChatGPT solution demonstrated using materials by the Orthopaedic Trauma Association.OTA international : the open access journal of orthopaedic trauma · 2025Article
- The Use of ChatGPT-4.0 to Simplify Breast Pathology Reports: A Study on Readability and Accuracy.Annals of surgical oncology · 2025Article
- Retrieval-augmented generation improves precision and trust of a GPT-4 model for emergency radiology diagnosis and classification: a proof-of-concept study.European radiology · 2025Article
- Health Consumers' Use and Perceptions of Health Information from Generative Artificial Intelligence Chatbots: A Scoping Review.Applied clinical informatics · 2025Article
- Decoding large language models for radiology: strategies for fine-tuning and prompt engineering.Radiology advances · 2025Review
- Areas of research focus and trends in the research on the application of AIGC in healthcare.Journal of health, population, and nutrition · 2025Article
- Evaluation of a large language model to simplify discharge summaries and provide cardiological lifestyle recommendations.Communications medicine · 2025Article
- Multi-view contrastive learning and symptom extraction insights for medical report generation.Scientific reports · 2025Article
- [Optimized interaction with Large Language Models : A practical guide to Prompt Engineering and Retrieval-Augmented Generation].Radiologie (Heidelberg, Germany) · 2025Review
- Assessing ChatGPT's summarization ofAbdominal radiology (New York) · 2025Article
- Performance of Large Language Models ChatGPT and Gemini on Workplace Management Questions in Radiology.Diagnostics (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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Abstract
purposeThe aim of this prospective cohort study was to assess the factual accuracy, completeness of medical information, and potential harmfulness of incorrect conclusions by medical professionals in automatically generated texts of varying complexity (1) using ChatGPT, Furthermore, patients without a medical background were asked to evaluate comprehensibility, information density, and conclusion possibilities (2).
methodsIn the study, five different simplified versions of MRI findings of the knee of different complexity (A: simple, B: moderate, C: complex) were each created using ChatGPT. Subsequently, a group of four medical professionals (two orthopedic surgeons and two radiologists) and a group of 20 consecutive patients evaluated the created reports. For this purpose, all participants received a group of simplified reports (simple, moderate, and severe) at intervals of 1 week each for their respective evaluation using a specific questionnaire. Each questionnaire consisted of the original report, the simplified report, and a series of statements to assess the quality of the simplified reports. Participants were asked to rate their level of agreement with a five-point Likert scale.
resultsThe evaluation of the medical specialists showed that the findings produced were consistent in quality depending on their complexity. Factual correctness, reproduction of relevant information and comprehensibility for patients were rated on average as "Agree". The question about possible harm resulted in an average of "Disagree". The evaluation of patients also revealed consistent quality of reports, depending on complexity. Simplicity of word choice and sentence structure was rated "Agree" on average, with significant differences between simple and complex findings (p = 0.0039) as well as between moderate and complex findings (p = 0.0222). Participants reported being significantly better at knowing what the text was about (p = 0.001) and drawing the correct conclusions the more simplified the report of findings was (p = 0.013829). The question of whether the text informed them as well as a healthcare professional was answered as "Neutral" across all findings.
conclusionBy using ChatGPT, MRI reports can be simplified automatically with consistent quality so that the relevant information is understandable to patients. However, a report generated in this way does not replace a thorough discussion between specialist and patient.
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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.