TY - JOUR T1 - Artificial intelligence to diagnose ear disease using otoscopic image analysis: a review JF - Journal of Investigative Medicine JO - J Investig Med SP - 354 LP - 362 DO - 10.1136/jim-2021-001870 VL - 70 IS - 2 AU - Therese L Canares AU - Weiyao Wang AU - Mathias Unberath AU - James H Clark Y1 - 2022/02/01 UR - http://hw-f5-jim.highwire.org/content/70/2/354.abstract N2 - 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. ER -