ArticleHealthcare (Basel, Switzerland)2024
Artificial Intelligence in Postoperative Care: Assessing Large Language Models for Patient Recommendations in Plastic Surgery.
Article in Healthcare (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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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.
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Who cites it
16 citing papers in PubMed.
- Comparative Evaluation of Large Language Models in the Recognition of Postoperative Complications Following Aesthetic Surgery.Aesthetic plastic surgery · 2026Article
- Fine-Tuning, Retrieval-Augmented Generation, and Hybrid Large Language Models for Postoperative Decision Support: Comparative Analysis.Journal of medical Internet research · 2026Article
- Assessing ChatGPT and Gemini Responses to Common Patient Questions Regarding Augmentation Mammaplasty.Aesthetic plastic surgery · 2026Article
- Assessing ChatGPT and Gemini Responses to Common Patient Questions Regarding Augmentation Mammaplasty.Aesthetic plastic surgery · 2026Article
- Automated Discharge Instructions in Medical and Surgical Care: A Systematic Review of Patient Engagement and Clinical Outcomes.Healthcare (Basel, Switzerland) · 2026Review
- The Development and Evaluation of a Retrieval-Augmented Generation Large Language Model Virtual Assistant for Postoperative Instructions.Bioengineering (Basel, Switzerland) · 2025Article
- Comparative evaluation of large language models in delivering guideline-compliant recommendations for topical NSAID use in musculoskeletal pain: a multidimensional analysis.Clinical rheumatology · 2025Article
- Evaluating the Competence of AI Chatbots in Answering Patient-Oriented Frequently Asked Questions on Orthognathic Surgery.Healthcare (Basel, Switzerland) · 2025Article
- Accuracy and Safety of ChatGPT-3.5 in Assessing Over-the-Counter Medication Use During Pregnancy: A Descriptive Comparative Study.Pharmacy (Basel, Switzerland) · 2025Article
- From Data to Decisions: Leveraging Retrieval-Augmented Generation to Balance Citation Bias in Burn Management Literature.European burn journal · 2025Article
- Performance of Artificial Intelligence in Addressing Questions Regarding the Management of Pediatric Supracondylar Humerus Fractures.Journal of the Pediatric Orthopaedic Society of North America · 2025Article
- The Future of Healthcare Is Digital: Unlocking the Potential of Mobile Health and E-Health Solutions.Healthcare (Basel, Switzerland) · 2025Article
- Artificial Intelligence in Breast Reconstruction: A Narrative Review.Medicina (Kaunas, Lithuania) · 2025Review
- Artificial Intelligence in Breast Cancer Diagnosis and Surgical Decision-Making: An Updated and Comprehensive Overview of Precision and Personalization in Current Evidence.Cancer management and research · 2025Review
- Using Large Language Models to Retrieve Critical Data from Clinical Processes and Business Rules.Bioengineering (Basel, Switzerland) · 2024Article
- Evaluation of the integration of retrieval-augmented generation in large language model for breast cancer nursing care responses.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Since their release, the medical community has been actively exploring large language models' (LLMs) capabilities, which show promise in providing accurate medical knowledge. One potential application is as a patient resource. This study analyzes and compares the ability of the currently available LLMs, ChatGPT-3.5, GPT-4, and Gemini, to provide postoperative care recommendations to plastic surgery patients. We presented each model with 32 questions addressing common patient concerns after surgical cosmetic procedures and evaluated the medical accuracy, readability, understandability, and actionability of the models' responses. The three LLMs provided equally accurate information, with GPT-3.5 averaging the highest on the Likert scale (LS) (4.18 ± 0.93) (
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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.