ReviewCureus2023
ChatGPT in Radiology: The Advantages and Limitations of Artificial Intelligence for Medical Imaging Diagnosis.
Review in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 2 of them syntheses that pooled it.
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
49 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Diagnostic performance of artificial intelligence based on contrast-enhanced computed tomography in pancreatic ductal adenocarcinoma: a systematic review and meta-analysis.Abdominal radiology (New York) · 2026Pooled it
- Pooled it
- Evaluating the Performance of ChatGPT-4V in Detecting Inflammatory Magnetic Resonance Imaging Findings of Sacroiliitis: Potentials, Challenges, and Limitations.Journal of imaging informatics in medicine · 2026Article
- Automated detection of periapical lesions in pediatric panoramic radiographs using YOLOv7: a retrospective internal validation study.BMC pediatrics · 2026Article
- Large Language Model-Generated Differential Diagnoses in Radiology Education: Comparison with a Standard Casebook.Diagnostics (Basel, Switzerland) · 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
- Impact of Large Language Model Assistance on Radiologists' Diagnostic Performance for Brain Tumors by Experience Level.Journal of clinical medicine · 2026Article
- Vision language models for scientific image analysis: an evaluation highlighting opportunities and challenges.npj computational materials · 2026Article
- Evaluating the clinical utility of multimodal large language models in rare maculopathy.Scientific reports · 2025Article
- Images Versus Videos in Contrast-Enhanced Ultrasound for Computer-Aided Diagnosis.Sensors (Basel, Switzerland) · 2025Article
- RadCLIP: Enhancing Radiologic Image Analysis Through Contrastive Language-Image Pretraining.IEEE transactions on neural networks and learning systems · 2025Article
- Artificial Intelligence in the Diagnosis and Imaging-Based Assessment of Pelvic Organ Prolapse: A Scoping Review.Medicina (Kaunas, Lithuania) · 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
- Economic Evaluation of Artificially Intelligent (AI) Diagnostic Systems: Cost Consequence Analysis of Clinician-Friendly Interpretable Computer-Aided Diagnosis (ICADX) Tested in Cardiology, Obstetrics, and Gastroenterology, from the HosmartAI Horizon 2020 Project.Healthcare (Basel, Switzerland) · 2025Article
- Article
- Large language models' capabilities in responding to tuberculosis medical questions: testing ChatGPT, Gemini, and Copilot.Scientific reports · 2025Article
- Article
- Artificial Intelligence in Chest Radiography-A Comparative Review of Human and Veterinary Medicine.Veterinary sciences · 2025Review
- Revolution or risk?-Assessing the potential and challenges of GPT-4V in radiologic image interpretation.European radiology · 2025Article
- Assessing Familiarity, Usage Patterns, and Attitudes of Medical Students Toward ChatGPT and Other Chat-Based AI Apps in Medical Education: Cross-Sectional Questionnaire Study.JMIR medical education · 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review article provides an overview of using artificial intelligence (AI) in radiology. It discusses the advantages and limitations of ChatGPT, a large language model, for medical imaging diagnosis. ChatGPT has shown great promise in improving the accuracy and efficiency of radiological diagnoses by reducing interpretation variability and errors and improving workflow efficiency. However, there are also limitations, including the need for high-quality training data, ethical considerations, and further research and development to improve its performance and usability. Despite these challenges, ChatGPT has the potential to significantly impact radiology and medical imaging diagnosis. The review article highlights the need for continued research and development, coupled with ethical and regulatory considerations, to ensure that ChatGPT is used to its full potential in improving radiological diagnoses and patient care.
Indexed as
Identifiers
What 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.