ArticleLaryngoscope investigative otolaryngology2024
Search for medical information for chronic rhinosinusitis through an artificial intelligence ChatBot.
Article in Laryngoscope investigative otolaryngology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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
2 citing papers in PubMed.
- Evaluation of AI Chatbot Responses to a Standardized Patient Query on Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease: Cross-Sectional Content Analysis.JMIR medical informatics · 2026Article
- Search for medical information for chronic rhinosinusitis through an artificial intelligence ChatBot.Laryngoscope investigative otolaryngology · 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
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: Artificial intelligence is evolving and significantly impacting health care, promising to transform access to medical information. With the rise of medical misinformation and frequent internet searches for health-related advice, there is a growing demand for reliable patient information. This study assesses the effectiveness of ChatGPT in providing information and treatment options for chronic rhinosinusitis (CRS). Methods: Six inputs were entered into ChatGPT regarding the definition, prevalence, causes, symptoms, treatment options, and postoperative complications of CRS. International Consensus Statement on Allergy and Rhinology guidelines for Rhinosinusitis was the gold standard for evaluating the answers. The inputs were categorized into three categories and Flesch-Kincaid readability, ANOVA and trend analysis tests were used to assess them. Results: Although some discrepancies were found regarding CRS, ChatGPT's answers were largely in line with existing literature. Mean Flesch Reading Ease, Flesch-Kincaid Grade Level and passive voice percentage were (40.7%, 12.15%, 22.5%) for basic information and prevalence category, (47.5%, 11.2%, 11.1%) for causes and symptoms category, (33.05%, 13.05%, 22.25%) for treatment and complications, and (40.42%, 12.13%, 18.62%) across all categories. ANOVA indicated no statistically significant differences in readability across the categories ( Conclusion: ChatGPT is a developing tool potentially useful for patients and medical professionals to access medical information. However, caution is advised as its answers may not be fully accurate compared to clinical guidelines or suitable for patients with varying educational backgrounds.Level of evidence: 4.
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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.