Literature DB >> 34521730

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

Therese L Canares1, Weiyao Wang2, Mathias Unberath2, James H Clark3.   

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. © American Federation for Medical Research 2022. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  diagnostic tests; ear; external; routine

Mesh:

Year:  2021        PMID: 34521730     DOI: 10.1136/jim-2021-001870

Source DB:  PubMed          Journal:  J Investig Med        ISSN: 1081-5589            Impact factor:   2.895


  1 in total

1.  Pediatric Otoscopy Video Screening With Shift Contrastive Anomaly Detection.

Authors:  Weiyao Wang; Aniruddha Tamhane; Christine Santos; John R Rzasa; James H Clark; Therese L Canares; Mathias Unberath
Journal:  Front Digit Health       Date:  2022-02-10
  1 in total

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