Artificial intelligence to diagnose ear disease using otoscopic image analysis: a review. (14th September 2021)

• Record Type: Journal Article
• Authors: Canares, Therese L; Wang, Weiyao; Unberath, Mathias; Clark, James H
• Is Part Of: Journal of investigative medicine. Volume 70:Number 2(2022)
• Page Start: 354
• Page End: 362
• Publication Date: 2021-09-14
• Subjects: ear -- external -- diagnostic tests -- routine; Clinical medicine -- Periodicals; Medicine -- Research -- Periodicals; Medicine; Research -- United States; Clinical medicine; Medicine -- Research; Periodicals; 616.075
• DOI: 10.1136/jim-2021-001870
• Languages: English
• ISSNs: 1081-5589

Abstract

Abstract : AI relates broadly to the science of developing computer systems to imitate human intelligence, thus allowing for the automation of tasks that would otherwise necessitate human cognition. Such technology has increasingly demonstrated capacity to outperform humans for functions relating to image recognition. Given the current lack of cost-effective confirmatory testing, accurate diagnosis and subsequent management depend on visual detection of characteristic findings during otoscope examination. The aim of this manuscript is to perform a comprehensive literature review and evaluate the potential application of artificial intelligence for the diagnosis of ear disease from otoscopic image analysis.