ReviewRadiologie (Heidelberg, Germany)2023
[Large language models such as ChatGPT and GPT-4 for patient-centered care in radiology].
Review in Radiologie (Heidelberg, Germany), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Evidence, use cases, and implementation safeguards of large language models in primary care.Communications medicine · 2026Review
- Evaluating Large Language Models in Interpreting MRI Reports and Recommending Treatment for Vestibular Schwannoma.Diagnostics (Basel, Switzerland) · 2025Article
- Article
- Evaluating GPT models for clinical note de-identification.Scientific reports · 2025Article
- Radiology Report Annotation Using Generative Large Language Models: Comparative Analysis.International journal of biomedical imaging · 2025Article
- ChatGPT in cardiovascular medicine: revolution, hype, or helper?Frontiers in public health · 2025Review
- AI in Dental Radiology-Improving the Efficiency of Reporting With ChatGPT: Comparative Study.Journal of medical Internet research · 2024Article
- Revolutionizing Radiology with Natural Language Processing and Chatbot Technologies: A Narrative Umbrella Review on Current Trends and Future Directions.Journal of clinical medicine · 2024Review
- ChatGPT utilization within the building blocks of the healthcare services: A mixed-methods study.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWith the introduction of ChatGPT in late November 2022, large language models based on artificial intelligence have gained worldwide recognition. These language models are trained on vast amounts of data, enabling them to process complex tasks in seconds and provide detailed, high-level text-based responses.
objectiveTo provide an overview of the most widely discussed large language models, ChatGPT and GPT‑4, with a focus on potential applications for patient-centered radiology. MATERIALS AND
methodsA PubMed search of both large language models was performed using the terms "ChatGPT" and "GPT-4", with subjective selection and completion in the form of a narrative review.
resultsThe generic nature of language models holds great promise for radiology, enabling both patients and referrers to facilitate understanding of radiological findings, overcome language barriers, and improve the quality of informed consent discussions. This could represent a significant step towards patient-centered or person-centered radiology.
conclusionLarge language models represent a promising tool for improving the communication of findings, interdisciplinary collaboration, and workflow in radiology. However, important privacy issues and the reliable applicability of these models in medicine remain to be addressed.
Indexed as
Identifiers
37615692What OpenQuestion holds
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.