Automated Diagnosis of Otitis Media: Vocabulary and Grammar
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 effus...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2013/327515 |
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| _version_ | 1832562558339383296 |
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| author | Anupama Kuruvilla Nader Shaikh Alejandro Hoberman Jelena Kovačević |
| author_facet | Anupama Kuruvilla Nader Shaikh Alejandro Hoberman Jelena Kovačević |
| author_sort | Anupama Kuruvilla |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-ba3087069ec1403fb86cf05baefa6064 |
| institution | Kabale University |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-ba3087069ec1403fb86cf05baefa60642025-02-03T01:22:23ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962013-01-01201310.1155/2013/327515327515Automated Diagnosis of Otitis Media: Vocabulary and GrammarAnupama Kuruvilla0Nader Shaikh1Alejandro Hoberman2Jelena Kovačević3Department of BME and Center for Bioimage Informatics, Carnegie Mellon University, Pittsburgh, PA 15213, USADivision of General Academic Pediatrics, Children’s Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USADivision of General Academic Pediatrics, Children’s Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USADepartment of BME and Center for Bioimage Informatics, Carnegie Mellon University, Pittsburgh, PA 15213, USAWe 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.http://dx.doi.org/10.1155/2013/327515 |
| spellingShingle | Anupama Kuruvilla Nader Shaikh Alejandro Hoberman Jelena Kovačević Automated Diagnosis of Otitis Media: Vocabulary and Grammar International Journal of Biomedical Imaging |
| title | Automated Diagnosis of Otitis Media: Vocabulary and Grammar |
| title_full | Automated Diagnosis of Otitis Media: Vocabulary and Grammar |
| title_fullStr | Automated Diagnosis of Otitis Media: Vocabulary and Grammar |
| title_full_unstemmed | Automated Diagnosis of Otitis Media: Vocabulary and Grammar |
| title_short | Automated Diagnosis of Otitis Media: Vocabulary and Grammar |
| title_sort | automated diagnosis of otitis media vocabulary and grammar |
| url | http://dx.doi.org/10.1155/2013/327515 |
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