Automated diagnosis of otitis media: Vocabulary and grammar

Anupama Kuruvilla, Nader Shaikh, Alejandro Hoberman, Jelena Kovacevic

Research output: Contribution to journalArticle

Abstract

We propose a novel automated algorithm for classifying diagnostic categories of otitis media: acute otitis media, otitis media with effusion, and no effusion. Acute otitis media represents a bacterial superinfection of the middle ear fluid, while otitis media with effusion represents a sterile effusion that tends to subside spontaneously. Diagnosing children with acute otitis media is difficult, often leading to overprescription of antibiotics as they are beneficial only for children with acute otitis media. This underscores the need for an accurate and automated diagnostic algorithm. To that end, we design a feature set understood by both otoscopists and engineers based on the actual visual cues used by otoscopists; we term this the otitis media vocabulary. We also design a process to combine the vocabulary terms based on the decision process used by otoscopists; we term this the otitis media grammar. The algorithm achieves 89.9% classification accuracy, outperforming both clinicians who did not receive special training and state-of-the-art classifiers.

Original languageEnglish (US)
Article number327515
JournalInternational Journal of Biomedical Imaging
Volume2013
DOIs
StatePublished - Sep 3 2013

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Vocabulary
Otitis Media
Otitis Media with Effusion
Superinfection
Middle Ear
Cues
Anti-Bacterial Agents

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

Automated diagnosis of otitis media : Vocabulary and grammar. / Kuruvilla, Anupama; Shaikh, Nader; Hoberman, Alejandro; Kovacevic, Jelena.

In: International Journal of Biomedical Imaging, Vol. 2013, 327515, 03.09.2013.

Research output: Contribution to journalArticle

Kuruvilla, Anupama ; Shaikh, Nader ; Hoberman, Alejandro ; Kovacevic, Jelena. / Automated diagnosis of otitis media : Vocabulary and grammar. In: International Journal of Biomedical Imaging. 2013 ; Vol. 2013.
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