ArticleAesthetic surgery journal. Open forum2023
Comparing the Efficacy of Large Language Models ChatGPT, BARD, and Bing AI in Providing Information on Rhinoplasty: An Observational Study.
Article in Aesthetic surgery journal. Open forum, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 4 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
34 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Comparison of the readability of ChatGPT and Bard in medical communication: a meta-analysis.BMC medical informatics and decision making · 2025Pooled it
- Evaluating the Clinical Utility of Robotic Systems in Plastic and Reconstructive Surgery: A Systematic Review.Sensors (Basel, Switzerland) · 2025Pooled 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
- Utility of Large Language Models for Congenital Microtia Reconstruction Education: Comparison of the Performance of Claude, GPT, and Gemini.Aesthetic plastic surgery · 2026Article
- The Role of Chatbots in Enquiry-Based Learning for Oral Health Students-An Exploratory Study.European journal of dental education : official journal of the Association for Dental Education in Europe · 2026Article
- Article
- The application and challenges of ChatGPT in laboratory medicine.Advances in laboratory medicine · 2025Review
- Artificial Intelligence Can Answer Postoperative Questions About Distal Radius Fractures-But Can Patients Understand the Answers?Journal of hand surgery global online · 2025Article
- Article
- Microsoft Copilot Provides More Accurate and Reliable Information About Anterior Cruciate Ligament Injury and Repair Than ChatGPT and Google Gemini; However, No Resource Was Overall the Best.Arthroscopy, sports medicine, and rehabilitation · 2025Article
- Management of Dupuytren's Disease: A Multi-Centric Comparative Analysis Between Experienced Hand Surgeons Versus Artificial Intelligence.Diagnostics (Basel, Switzerland) · 2025Article
- Current applications and challenges in large language models for patient care: a systematic review.Communications medicine · 2025Article
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- Article
- Exploring the Potential of an AI Chatbot as a Supplementary Tool for Nutritional Prescription Hospital Discharge: A Preliminary Study.Scientifica · 2025Article
- Assessment of the information quality of chatbot technologies on orthodontic miniscrews.Dental press journal of orthodontics · 2025Article
- Assessment of Large Language Models (LLMs) in decision-making support for gynecologic oncology.Computational and structural biotechnology journal · 2024Article
- Can AI Answer My Questions? Utilizing Artificial Intelligence in the Perioperative Assessment for Abdominoplasty Patients.Aesthetic plastic surgery · 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
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Large language models (LLMs) are emerging artificial intelligence (AI) technologies refining research and healthcare. However, the impact of these models on presurgical planning and education remains under-explored. Objectives: This study aims to assess 3 prominent LLMs-Google's AI BARD (Mountain View, CA), Bing AI (Microsoft, Redmond, WA), and ChatGPT-3.5 (Open AI, San Francisco, CA) in providing safe medical information for rhinoplasty. Methods: Six questions regarding rhinoplasty were prompted to ChatGPT, BARD, and Bing AI. A Likert scale was used to evaluate these responses by a panel of Specialist Plastic and Reconstructive Surgeons with extensive experience in rhinoplasty. To measure reliability, the Flesch Reading Ease Score, the Flesch-Kincaid Grade Level, and the Coleman-Liau Index were used. The modified DISCERN score was chosen as the criterion for assessing suitability and reliability. A Results: In terms of reliability, BARD and ChatGPT demonstrated a significantly ( Conclusions: BARD delivered the most succinct and comprehensible information, followed by ChatGPT and Bing AI. Although these models demonstrate potential, challenges regarding their depth and specificity remain. Therefore, future research should aim to augment LLM performance through the integration of specialized databases and expert knowledge, while also refining their algorithms. Level of Evidence 5:
Identifiers
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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.