A Scoping Review of Artificial Intelligence Research in Rhinology.

IF 2.5 3区 医学 Q1 OTORHINOLARYNGOLOGY American Journal of Rhinology & Allergy Pub Date : 2023-07-01 DOI:10.1177/19458924231162437
Gabriel Osie, Rhea Darbari Kaul, Raquel Alvarado, Gregory Katsoulotos, Janet Rimmer, Larry Kalish, Raewyn G Campbell, Raymond Sacks, Richard J Harvey
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引用次数: 1

Abstract

Background: A considerable volume of possible applications of artificial intelligence (AI) in the field of rhinology exists, and research in the area is rapidly evolving.

Objective: This scoping review aims to provide a brief overview of all current literature on AI in the field of rhinology. Further, it aims to highlight gaps in the literature for future rhinology researchers.

Methods: OVID MEDLINE (1946-2022) and EMBASE (1974-2022) were searched from January 1, 2017 until May 14, 2022 to identify all relevant articles. The Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews checklist was used to guide the review.

Results: A total of 2420 results were identified of which 62 met the eligibility criteria. A further 17 articles were included through bibliography searching, for a total of 79 articles on AI in rhinology. Each year resulted in an increase in the number of publications, from 3 articles published in 2017 to 31 articles published in 2021. Articles were produced by authors from 22 countries with a relative majority coming from the USA (19%), China (19%), and South Korea (13%). Articles were placed into 1 of 5 categories: phenotyping/endotyping (n = 12), radiological diagnostics (n = 42), prognostication (n = 10), non-radiological diagnostics (n = 7), surgical assessment/planning (n = 8). Diagnostic or prognostic utility of the AI algorithms were rated as excellent (n = 29), very good (n = 25), good (n = 7), sufficient (n = 1), bad (n = 2), or was not reported/not applicable (n = 15).

Conclusions: AI is experiencing an increasingly significant role in rhinology research. Articles are showing high rates of diagnostic accuracy and are being published at an almost exponential rate around the world. Utilizing AI in radiological diagnosis was the most published topic of research, however, AI in rhinology is still in its infancy and there are several topics yet to be thoroughly explored.

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鼻科学人工智能研究综述
背景:人工智能(AI)在鼻科学领域存在大量可能的应用,并且该领域的研究正在迅速发展。目的:本综述的目的是提供一个简短的概述所有当前文献的人工智能在鼻科学领域。此外,它旨在为未来的鼻科学研究人员强调文献中的空白。方法:检索2017年1月1日至2022年5月14日的OVID MEDLINE(1946-2022)和EMBASE(1974-2022),确定所有相关文章。系统评价和荟萃分析首选报告项目范围评价扩展清单用于指导评价。结果:共筛选到2420个结果,其中62个符合入选标准。通过文献检索,还收录了17篇文章,共计79篇关于人工智能在鼻科学中的应用。每年发表的文章数量都在增加,从2017年的3篇增加到2021年的31篇。文章的作者来自22个国家,其中相对多数来自美国(19%)、中国(19%)和韩国(13%)。文章被分为5类中的1类:表型/内源性分型(n = 12),放射诊断(n = 42),预后(n = 10),非放射诊断(n = 7),手术评估/计划(n = 8)。人工智能算法的诊断或预后效用被评为优秀(n = 29)、非常好(n = 25)、良好(n = 7)、足够(n = 1)、不好(n = 2)或未报告/不适用(n = 15)。结论:人工智能在鼻科学研究中的作用越来越重要。文章显示出很高的诊断准确率,并且在世界范围内以几乎指数级的速度发表。将人工智能应用于放射诊断是发表最多的研究课题,然而,人工智能在鼻科的应用仍处于起步阶段,还有几个课题有待深入探索。
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来源期刊
CiteScore
5.60
自引率
11.50%
发文量
82
审稿时长
4-8 weeks
期刊介绍: The American Journal of Rhinology & Allergy is a peer-reviewed, scientific publication committed to expanding knowledge and publishing the best clinical and basic research within the fields of Rhinology & Allergy. Its focus is to publish information which contributes to improved quality of care for patients with nasal and sinus disorders. Its primary readership consists of otolaryngologists, allergists, and plastic surgeons. Published material includes peer-reviewed original research, clinical trials, and review articles.
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