Alejandro R Marrero-Gonzalez, Tanner J Diemer, Shaun A Nguyen, Terence J M Camilon, Kirsten Meenan, Ashli O'Rourke
{"title":"人工智能在喉部病变中的应用：系统回顾与荟萃分析。","authors":"Alejandro R Marrero-Gonzalez, Tanner J Diemer, Shaun A Nguyen, Terence J M Camilon, Kirsten Meenan, Ashli O'Rourke","doi":"10.1007/s00405-024-09075-0","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>The objective of this systematic review and meta-analysis was to evaluate the diagnostic accuracy of AI-assisted technologies, including endoscopy, voice analysis, and histopathology, for detecting and classifying laryngeal lesions.</p><p><strong>Methods: </strong>A systematic search was conducted in PubMed, Embase, etc. for studies utilizing voice analysis, histopathology for laryngeal lesions, or AI-assisted endoscopy. The results of diagnostic accuracy, sensitivity and specificity were synthesized by a meta-analysis.</p><p><strong>Results: </strong>12 studies employing AI-assisted endoscopy, 2 studies for voice analysis, and 4 studies for histopathology were included in the meta-analysis. The combined sensitivity of AI-assisted endoscopy was 91% (95% CI 87-94%) for the classification of benign from malignant lesions and 91% (95% CI 90-93%) for lesion detection. The highest accuracy pooled in detecting lesions versus healthy tissue was the AI-aided endoscopy was 94% (95% CI 92-97%).</p><p><strong>Conclusions: </strong>For laryngeal lesions, AI-assisted endoscopy shows excellent diagnosis accuracy. But more sizable prospective trials are needed to confirm the practical clinical value.</p>","PeriodicalId":11952,"journal":{"name":"European Archives of Oto-Rhino-Laryngology","volume":" ","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of artificial intelligence in laryngeal lesions: a systematic review and meta-analysis.\",\"authors\":\"Alejandro R Marrero-Gonzalez, Tanner J Diemer, Shaun A Nguyen, Terence J M Camilon, Kirsten Meenan, Ashli O'Rourke\",\"doi\":\"10.1007/s00405-024-09075-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>The objective of this systematic review and meta-analysis was to evaluate the diagnostic accuracy of AI-assisted technologies, including endoscopy, voice analysis, and histopathology, for detecting and classifying laryngeal lesions.</p><p><strong>Methods: </strong>A systematic search was conducted in PubMed, Embase, etc. for studies utilizing voice analysis, histopathology for laryngeal lesions, or AI-assisted endoscopy. The results of diagnostic accuracy, sensitivity and specificity were synthesized by a meta-analysis.</p><p><strong>Results: </strong>12 studies employing AI-assisted endoscopy, 2 studies for voice analysis, and 4 studies for histopathology were included in the meta-analysis. The combined sensitivity of AI-assisted endoscopy was 91% (95% CI 87-94%) for the classification of benign from malignant lesions and 91% (95% CI 90-93%) for lesion detection. The highest accuracy pooled in detecting lesions versus healthy tissue was the AI-aided endoscopy was 94% (95% CI 92-97%).</p><p><strong>Conclusions: </strong>For laryngeal lesions, AI-assisted endoscopy shows excellent diagnosis accuracy. But more sizable prospective trials are needed to confirm the practical clinical value.</p>\",\"PeriodicalId\":11952,\"journal\":{\"name\":\"European Archives of Oto-Rhino-Laryngology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Archives of Oto-Rhino-Laryngology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00405-024-09075-0\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"OTORHINOLARYNGOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Archives of Oto-Rhino-Laryngology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00405-024-09075-0","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OTORHINOLARYNGOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
目的：本系统综述和荟萃分析旨在评估人工智能辅助技术（包括内窥镜检查、语音分析和组织病理学）在检测和分类喉部病变方面的诊断准确性：方法： 在PubMed、Embase等网站上对利用嗓音分析、喉部病变组织病理学或人工智能辅助内窥镜进行的研究进行了系统检索。通过荟萃分析综合了诊断准确性、敏感性和特异性的结果：荟萃分析共纳入了 12 项采用人工智能辅助内窥镜检查的研究、2 项语音分析研究和 4 项组织病理学研究。人工智能辅助内窥镜对良性与恶性病变分类的综合灵敏度为91%（95% CI 87-94%），对病变检测的综合灵敏度为91%（95% CI 90-93%）。人工智能辅助内窥镜检测病变与健康组织的综合准确率最高，为94%（95% CI 92-97%）：结论：对于喉部病变，人工智能辅助内窥镜检查显示出极佳的诊断准确性。结论：对于喉部病变，人工智能辅助内窥镜检查显示出极佳的诊断准确性，但还需要更大规模的前瞻性试验来证实其实际临床价值。
Application of artificial intelligence in laryngeal lesions: a systematic review and meta-analysis.
Objective: The objective of this systematic review and meta-analysis was to evaluate the diagnostic accuracy of AI-assisted technologies, including endoscopy, voice analysis, and histopathology, for detecting and classifying laryngeal lesions.
Methods: A systematic search was conducted in PubMed, Embase, etc. for studies utilizing voice analysis, histopathology for laryngeal lesions, or AI-assisted endoscopy. The results of diagnostic accuracy, sensitivity and specificity were synthesized by a meta-analysis.
Results: 12 studies employing AI-assisted endoscopy, 2 studies for voice analysis, and 4 studies for histopathology were included in the meta-analysis. The combined sensitivity of AI-assisted endoscopy was 91% (95% CI 87-94%) for the classification of benign from malignant lesions and 91% (95% CI 90-93%) for lesion detection. The highest accuracy pooled in detecting lesions versus healthy tissue was the AI-aided endoscopy was 94% (95% CI 92-97%).
Conclusions: For laryngeal lesions, AI-assisted endoscopy shows excellent diagnosis accuracy. But more sizable prospective trials are needed to confirm the practical clinical value.
期刊介绍：
Official Journal of
European Union of Medical Specialists – ORL Section and Board
Official Journal of Confederation of European Oto-Rhino-Laryngology Head and Neck Surgery
"European Archives of Oto-Rhino-Laryngology" publishes original clinical reports and clinically relevant experimental studies, as well as short communications presenting new results of special interest. With peer review by a respected international editorial board and prompt English-language publication, the journal provides rapid dissemination of information by authors from around the world. This particular feature makes it the journal of choice for readers who want to be informed about the continuing state of the art concerning basic sciences and the diagnosis and management of diseases of the head and neck on an international level.
European Archives of Oto-Rhino-Laryngology was founded in 1864 as "Archiv für Ohrenheilkunde" by A. von Tröltsch, A. Politzer and H. Schwartze.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
