@article {Canares354, author = {Therese L Canares and Weiyao Wang and Mathias Unberath and James H Clark}, title = {Artificial intelligence to diagnose ear disease using otoscopic image analysis: a review}, volume = {70}, number = {2}, pages = {354--362}, year = {2022}, doi = {10.1136/jim-2021-001870}, publisher = {BMJ Publishing Group Limited}, 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.}, issn = {1081-5589}, URL = {http://hw-f5-jim.highwire.org/content/70/2/354}, eprint = {http://hw-f5-jim.highwire.org/content/70/2/354.full.pdf}, journal = {Journal of Investigative Medicine} }