Search for medical information for chronic rhinosinusitis through an artificial intelligence ChatBot

Author:

Yassa Arsany1ORCID,Ayad Olivia234,Cohen David Avery5ORCID,Patel Aman M.1ORCID,Vengsarkar Ved A.1,Hegazin Michael S.1,Filimonov Andrey1ORCID,Hsueh Wayne D.167,Eloy Jean Anderson16789ORCID

Affiliation:

1. Department of Otolaryngology—Head and Neck Surgery Rutgers New Jersey Medical School Newark New Jersey USA

2. Department of Architecture and Territory Mediterranean University of Reggio Calabria Calabria Italy

3. Department of Landscape Architecture International Credit Hours Engineering Programs of Ain Shams University Cairo Egypt

4. Arclivia Bayonne NJ United States

5. Department of Otolaryngology—Head and Neck Surgery University of Florida College of Medicine Gainesville Florida USA

6. Department of Ophthalmology and Visual Science Rutgers New Jersey Medical School Newark New Jersey USA

7. Center for Skull Base and Pituitary Surgery, Neurological Institute of New Jersey Rutgers New Jersey Medical School Newark New Jersey USA

8. Department of Neurological Surgery Rutgers New Jersey Medical School Newark New Jersey USA

9. Department of Otolaryngology and Facial Plastic Surgery Cooperman Barnabas Medical Center—RWJBarnabas Health Livingston New Jersey USA

Abstract

AbstractObjectivesArtificial 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).MethodsSix 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.ResultsAlthough 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 (p‐values: Flesch Reading Ease = 0.385, Flesch–Kincaid Grade Level = 0.555, Passive Sentences = 0.601). Trend analysis revealed readability varied slightly, with a general increase in complexity.ConclusionChatGPT 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.

Publisher

Wiley

Reference54 articles.

1. The potential for artificial intelligence in healthcare;Wen Z;J Commer Biotechnol,2022

2. A compendium of various applications of machine learning;Siwach M;Int J Res Eng Technol,2022

3. Empirical Approach to Machine Learning

4. MohammadSM.Ethics sheets for AI tasks.arXiv preprint arXiv:2107.011832021.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3