ArticleDigital health
Feasibility and acceptability of ChatGPT generated radiology report summaries for cancer patients.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.
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Who cites it
26 citing papers in PubMed, 2 syntheses or guidelines 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
- Testing and Evaluation of Health Care Applications of Large Language Models: A Systematic Review.JAMA · 2025Pooled it
- Assessing the clinical applicability of large language models for microwave ablation guidance.European journal of radiology open · 2026Article
- Applications, Challenges, and Future Directions of Large Language Models in Health Care Communication: Scoping Review.Journal of medical Internet research · 2026Article
- LLMs as emerging tools for understanding and managing bone metastasis and cancer-induced bone pain.iScience · 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
- Optimization of University Counseling Consent Forms With Large Language Models: Multidimensional Comparative Evaluation.Journal of medical Internet research · 2026Article
- Fight for the People's Health: The Application of Al Multiagent Systems in Medical Consortia.Health care science · 2026Review
- Current Applications and Future Directions of Artificial Intelligence in Prostate Cancer Diagnosis: A Narrative Review.Current oncology (Toronto, Ont.) · 2026Review
- Case-matched retrieval improves textual alignment of LLM-generated radiology impressions.PloS one · 2026Article
- Enhancing Patient Understanding of Perianal Fistula MRI Findings Using ChatGPT: A Randomized, Single Centre Study.Diagnostics (Basel, Switzerland) · 2025Article
- Using large language models for clinical staging of colorectal cancer from imaging reports: a pilot study.Annals of surgical treatment and research · 2025Article
- Evaluating the Quality and Understandability of Radiology Report Summaries Generated by ChatGPT: Survey Study.JMIR formative research · 2025Article
- Review
- Development and evaluation of large-language models (LLMs) for oncology: A scoping review.PLOS digital health · 2025Article
- Large language model integrations in cancer decision-making: a systematic review and meta-analysis.NPJ digital medicine · 2025Article
- 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
- Patients' Attitudes to Magnetic Resonance Imaging in Perianal Fistulizing Crohn's Disease: A Global Survey.Crohn's & colitis 360 · 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Patients now have direct access to their radiology reports, which can include complex terminology and be difficult to understand. We assessed ChatGPT's ability to generate summarized MRI reports for patients with prostate cancer and evaluated physician satisfaction with the artificial intelligence (AI)-summarized report. Methods: We used ChatGPT to summarize five full MRI reports for patients with prostate cancer performed at a single institution from 2021 to 2022. Three summarized reports were generated for each full MRI report. Full MRI and summarized reports were assessed for readability using Flesch-Kincaid Grade Level (FK) score. Radiation oncologists were asked to evaluate the AI-summarized reports via an anonymous questionnaire. Qualitative responses were given on a 1-5 Likert-type scale. Fifty newly diagnosed prostate cancer patient MRIs performed at a single institution were additionally assessed for physician online portal response rates. Results: Fifteen summarized reports were generated from five full MRI reports using ChatGPT. The median FK score for the full MRI reports and summarized reports was 9.6 vs. 5.0, ( Conclusions: We demonstrate a novel application of ChatGPT to summarize MRI reports at a reading level appropriate for patients. Physicians were likely to be satisfied with the summarized reports with respect to factual correctness, ease of understanding, and completeness. Physicians were less likely to be satisfied with respect to potential for harm, overall quality, and likelihood to send to patients. Further research is needed to optimize ChatGPT's ability to summarize radiology reports and understand what factors influence physician trust in AI-summarized reports.
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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.