ReviewLa Radiologia medica2025
Hi ChatGPT, I am a Radiologist, How can you help me?
Review in La Radiologia medica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Adaptive Fast-Slow Large Language Model Framework for Multidimensional Classification of Prenatal Ultrasound Reports: Comparative Study.Journal of medical Internet research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review paper explores the integration of ChatGPT, a generative AI model developed by OpenAI, into radiological practices, focusing on its potential to enhance the operational efficiency of radiologists. ChatGPT operates on the GPT architecture, utilizing advanced machine learning techniques, including unsupervised pre-training and reinforcement learning, to generate human-like text responses. While AI applications in radiology predominantly focus on imaging acquisition, reconstruction, and interpretation-commonly embedded directly within hardware-the accessibility and functional breadth of ChatGPT make it a unique tool. This interview-based review should not be intended as a detailed evaluation of all ChatGPT features. Instead, it aims to test its utility in everyday radiological tasks through real-world examples. ChatGPT demonstrated strong capabilities in structuring radiology reports according to international guidelines (e.g., PI-RADS, CT reporting for diverticulitis), designing a complete research protocol, and performing advanced statistical analysis from Excel datasets, including ROC curve generation and intergroup comparison. Although not capable of directly interpreting DICOM images, ChatGPT provided meaningful assistance in image post-processing and interpretation when images were converted to standard formats. These findings highlight its current strengths and limitations as a supportive tool for radiologists.
Indexed as
Identifiers
40699279What 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.