ArticleCureus2023
Evaluation of ChatGPT's Capabilities in Medical Report Generation.
Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 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
42 citing papers in PubMed, 2 syntheses or guidelines pooled it, 82 citations in OpenAlex.
- Applications and Concerns of ChatGPT and Other Conversational Large Language Models in Health Care: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Exploring the role of ChatGPT in patient care (diagnosis and treatment) and medical research: A systematic review.Health promotion perspectives · 2023Pooled it
- Training Empathetic Communication Skills in Medical Students With a Role-Prompted GPT-4o Chatbot: Quasi-Experimental Intervention Study.JMIR medical education · 2026Article
- Evaluating the performance of ChatGPT in responding to myotonic dystrophy type 1 patient inquiries: a specialist physician-based study.BMC neurology · 2026Article
- Prioritising Data Quality Governance for AI in Prostate Cancer: A Methodological Proof-of-Concept Study Using Neural Networks for Risk Stratification.Diagnostics (Basel, Switzerland) · 2026Article
- Medicine digital transformation: evidence from Chinese physicians on generative artificial intelligence implementation and challenges.Journal of translational medicine · 2026Article
- Large Language Models in Randomized Controlled Trials Design: Observational Study.Journal of medical Internet research · 2025Observational
- Clinical applications of large language models in medicine and surgery: A scoping review.The Journal of international medical research · 2025Article
- Areas of research focus and trends in the research on the application of AIGC in healthcare.Journal of health, population, and nutrition · 2025Article
- ChatGPT's competence in responding to urological emergencies.Ulusal travma ve acil cerrahi dergisi = Turkish journal of trauma & emergency surgery : TJTES · 2025Article
- Evaluation of the Performance of Three Large Language Models in Clinical Decision Support: A Comparative Study Based on Actual Cases.Journal of medical systems · 2025Article
- Comparison of the performances between ChatGPT and Gemini in answering questions on viral hepatitis.Scientific reports · 2025Article
- Is your curriculum GenAI-proof? A method for GenAI impact assessment and a case study.MedEdPublish (2016) · 2025Article
- ChatGPT's Role in Coronary Artery Bypass Graft Information: A Critical Assessment.Sisli Etfal Hastanesi tip bulteni · 2025Article
- Assessing the ability of ChatGPT 4.0 in generating check-up reports.Frontiers in medicine · 2025Article
- Benefits, limits, and risks of ChatGPT in medicine.Frontiers in artificial intelligence · 2025Review
- Exploring ChatGPT in clinical inquiry: a scoping review of characteristics, applications, challenges, and evaluation.Annals of medicine and surgery (2012) · 2024Article
- Understanding AI's Role in Endometriosis Patient Education and Evaluating Its Information and Accuracy: Systematic Review.JMIR AI · 2024Review
- The transformative impact of large language models on medical writing and publishing: current applications, challenges and future directions.The Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2024Review
- Educational Utility of Clinical Vignettes Generated in Japanese by ChatGPT-4: Mixed Methods Study.JMIR medical education · 2024Article
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 at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The growing demand for efficient healthcare delivery has intensified the need for technological innovations that facilitate medical professionals' decision-making processes. In this study, we investigate ChatGPT (OpenAI Incorporated, Mission District, San Francisco, United States), a state-of-the-art language model based on the GPT-4 architecture, as an effective tool for assisting healthcare professionals in writing medical reports based on real patient laboratory results. By leveraging ChatGPT's extraordinary performance across multiple medical domains, including lab result diagnostics and medical literature analysis, we aimed to streamline and enhance the medical report generation process. The generated case report presents a 31-year-old male patient with no significant past medical history who visited a clinic to establish care and seek evaluation for abdominal pain. Following routine laboratory tests, including a complete blood count, comprehensive metabolic panel, and a Helicobacter pylori breath test, ChatGPT provided tailored recommendations addressing identified concerns and abnormalities. These included lifestyle modifications, such as dietary changes, weight management, and avoiding trigger foods or behaviors; alongside medical treatment options, the patient was advised to consult a gastroenterologist for further evaluation and potential advanced treatment options. The organization and structure of this case study are derived from ChatGPT's output, using patient's actual physical information and lab results as input, without any prior knowledge. Ultimately, we will compare the generated report with suggestions from an online doctor consultation system to demonstrate the precision and reliability of ChatGPT's recommendations. Through this comparison, we aim to show that ChatGPT can produce coherent, comprehensive, and clinically relevant medical reports with a relatively high degree of accuracy and consistency.
Indexed as
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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.