ArticleCureus2023
Efficacy of AI Chats to Determine an Emergency: A Comparison Between OpenAI's ChatGPT, Google Bard, and Microsoft Bing AI Chat.
Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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
27 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Large Language Models for Chatbot Health Advice Studies: A Systematic Review.JAMA network open · 2025Pooled it
- Comparative analysis of ChatGPT and Gemini (Bard) in medical inquiry: a scoping review.Frontiers in digital health · 2025Pooled it
- Preliminary evaluation of ChatGPT model iterations in emergency department diagnostics.Scientific reports · 2025Article
- Quality of Chatbot Responses to the Most Popular Questions Regarding Erectile Dysfunction.Urology research & practice · 2025Article
- Exploring the Potential of an AI Chatbot as a Supplementary Tool for Nutritional Prescription Hospital Discharge: A Preliminary Study.Scientifica · 2025Article
- Assessment of Large Language Models (LLMs) in decision-making support for gynecologic oncology.Computational and structural biotechnology journal · 2024Article
- Analyzing evaluation methods for large language models in the medical field: a scoping review.BMC medical informatics and decision making · 2024Article
- Accuracy of Prospective Assessments of 4 Large Language Model Chatbot Responses to Patient Questions About Emergency Care: Experimental Comparative Study.Journal of medical Internet research · 2024Article
- "Doctor ChatGPT, Can You Help Me?" The Patient's Perspective: Cross-Sectional Study.Journal of medical Internet research · 2024Article
- Evaluating the efficacy of leading large language models in the Japanese national dental hygienist examination: A comparative analysis of ChatGPT, Bard, and Bing Chat.Journal of dental sciences · 2024Article
- eHealth Assistant AI Chatbot Using a Large Language Model to Provide Personalized Answers through Secure Decentralized Communication.Sensors (Basel, Switzerland) · 2024Article
- Ethical Considerations and Fundamental Principles of Large Language Models in Medical Education: Viewpoint.Journal of medical Internet research · 2024Article
- Impact of Large Language Models on Medical Education and Teaching Adaptations.JMIR medical informatics · 2024Article
- Disparities in medical recommendations from AI-based chatbots across different countries/regions.Scientific reports · 2024Article
- Exploring the Role of ChatGPT-4, BingAI, and Gemini as Virtual Consultants to Educate Families about Retinopathy of Prematurity.Children (Basel, Switzerland) · 2024Article
- AI in Hand Surgery: Assessing Large Language Models in the Classification and Management of Hand Injuries.Journal of clinical medicine · 2024Article
- Comparison of Large Language Models in Answering Immuno-Oncology Questions: A Cross-Sectional Study.The oncologist · 2024Article
- Article
- Evaluating human resources management literacy: A performance analysis of ChatGPT and bard.Heliyon · 2024Article
- Integrating Retrieval-Augmented Generation with Large Language Models in Nephrology: Advancing Practical Applications.Medicina (Kaunas, Lithuania) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background The escalating overload and saturation of emergency services, primarily caused by non-urgent cases overwhelming the system, have spurred a critical necessity for innovative solutions that can effectively differentiate genuine emergencies from situations that could be managed through alternative means, such as using AI chatbots. This study aims to evaluate and compare the accuracy in differentiating between a medical emergency and a non-emergency of three of the most popular AI chatbots at the moment. Methods In this study, patient questions from the online forum r/AskDocs on Reddit were collected to determine whether their clinical cases were emergencies. A total of 176 questions were reviewed by the authors, with 75 deemed emergencies and 101 non-emergencies. These questions were then posed to AI chatbots, including ChatGPT, Google Bard, and Microsoft Bing AI, with their responses evaluated against each other and the authors' responses. A criteria-based system categorized the AI chatbot answers as "yes," "no," or "cannot determine." The performance of each AI chatbot was compared in both emergency and non-emergency cases, and statistical analysis was conducted to assess the significance of differences in their performance. Results In general, AI chatbots considered around 12-15% more cases to be an emergency than reviewers, while they considered a very low number of cases as non-emergency compared to reviewers (around 35% fewer cases). Google Bard detected the most true emergency cases (87%) and true non-emergency cases (36%). However, no real difference in performance between the three AI chatbots was found in detecting true emergencies (p-value = 0.35) and non-emergency cases (p-value = 0.16). Conclusions These AI systems require further refinement to identify emergency situations accurately, but they could potentially be an innovative tool for emergency care and improving patient outcomes. The integration of AI chatbots like ChatGPT, Google Bard, and Microsoft Bing Chat offers a promising avenue to mitigate ED strain and enhance emergency management.
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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.