Artificial intelligence to diagnose ear disease using otoscopic image analysis: a review

Therese Canares; Weiyao Wang; Mathias Unberath; James H. Clark

doi:10.1136/jim-2021-001870

Artificial intelligence to diagnose ear disease using otoscopic image analysis: a review

Therese Canares, Weiyao Wang, Mathias Unberath, James H. Clark

School of Medicine

Research output: Contribution to journal › Review article › peer-review

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.

Original language	English (US)
Pages (from-to)	354-362
Number of pages	9
Journal	Journal of investigative medicine : the official publication of the American Federation for Clinical Research
Volume	70
Issue number	2
DOIs	https://doi.org/10.1136/jim-2021-001870
State	Published - Feb 1 2022

Keywords

diagnostic tests
ear
external
routine

ASJC Scopus subject areas

General Biochemistry, Genetics and Molecular Biology

Access to Document

10.1136/jim-2021-001870

Cite this

Artificial intelligence to diagnose ear disease using otoscopic image analysis: a review. / Canares, Therese; Wang, Weiyao; Unberath, Mathias et al.
In: Journal of investigative medicine : the official publication of the American Federation for Clinical Research, Vol. 70, No. 2, 01.02.2022, p. 354-362.

Research output: Contribution to journal › Review article › peer-review

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Artificial intelligence to diagnose ear disease using otoscopic image analysis: a review

Abstract

Keywords

ASJC Scopus subject areas

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