ArticleAbdominal radiology (New York)2025
Assessing ChatGPT's summarization of
Article in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Staging Prostate Cancer with AI: A Comparative Study of Large Language Models and Expert Interpretation on PSMA PET-CT Reports.Molecular imaging and biology · 2026Article
- Artificial intelligence can match domain experts in evidence extraction and critical appraisal of microbial oncogenesis research publications.Frontiers in cellular and infection microbiology · 2026Article
- Assessment of the validity of ChatGPT-3.5 responses to patient-generated queries following BPH surgery.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeChatGPT has recently been the subject of many studies, and its responses to medical questions have been successful. We examined ChatGPT-4's evaluation of structured
methods
resultsThe mean scores for clarity were 4.93 ± 0.32, 4.95 ± 0.25, 4.96 ± 0.19, 4.99 ± 0.11, and 4.96 ± 0.30, respectively. The mean scores for accuracy were 4.87 ∓ 0.61, 4.87 ∓ 0.62, 4.79 ± 0.83, 4.96 ± 0.25, and 4.93 ± 0.45, respectively. Patients with distant lymphatic metastases had a lower mean accuracy score than those without (4.28 ± 1.45 vs. 4.94 ± 0.39; p < 0.001). ChatGPT-4's responses in 13 patients (8%) had the potential for harmful information.
conclusionChatGPT-4 successfully interprets structured
Indexed as
Identifiers
39347975What 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.