How advantageous is it to use computed tomography image-based artificial intelligence modelling in the differential diagnosis of chronic otitis media with and without cholesteatoma?

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dc.authorid0000-0002-2421-4842en_US
dc.authorid0000-0002-0060-1880en_US
dc.authorid0000-0002-3402-2625en_US
dc.contributor.authorAyral, Muhammed
dc.contributor.authorTürk, Ömer
dc.contributor.authorCan, Şermin
dc.contributor.authorEsen, D.
dc.contributor.authorTopçu, İsmail
dc.contributor.authorAkıl, Ferit
dc.contributor.authorTemiz, Hakan
dc.date.accessioned2023-08-08T13:17:57Z
dc.date.available2023-08-08T13:17:57Z
dc.date.issued2023en_US
dc.departmentDicle Üniversitesi, Tıp Fakültesi, Cerrahi Tıp Bilimleri Bölümü, Kulak Burun ve Boğaz Hastalıkları Ana Bilim Dalıen_US
dc.description.abstractOBJECTIVE: Cholesteatoma (CHO) developing secondary to chronic otitis media (COM) can spread rapidly and cause important health problems such as hearing loss. Therefore, the presence of CHO should be diagnosed promptly with high accuracy and then treated surgically. The aim of this study was to investigate the effectiveness of artificial intelligence applications (AIA) in documenting the presence of CHO based on computed tomography (CT) images. PATIENTS AND METHODS: The study was performed on CT images of 100 CHO, 100 non-cholesteatoma (N-CHO) COM, and 100 control patients. Two AIA models including Res-Net50 and MobileNetV2 were used for the classification of the images. RESULTS: Overall accuracy rate was 93.33% for the ResNet50 model and 86.67% for the MobilNetV2 model. Moreover, the diagnostic accuracy rates of these two models were 100% and 95% in the CHO group, 90% and 85% in the N-CHO group, and 90% and 80% in the control group, respectively. CONCLUSIONS: These results indicate that the use of AIA in the diagnosis of CHO will improve the diagnostic accuracy rates and will also help physicians in terms of reducing their workload and facilitating the selection of the correct treatment strategy.en_US
dc.identifier.citationAyral, M., Türk, Ö., Can, Ş., Esen, D., Topçu, İ., Akıl, F. ve diğerleri. (2023). How advantageous is it to use computed tomography image-based artificial intelligence modelling in the differential diagnosis of chronic otitis media with and without cholesteatoma?. European Review for Medical and Pharmacological Sciences, 27(1), 215-223.en_US
dc.identifier.doi10.26355/eurrev_202301_30874
dc.identifier.endpage223en_US
dc.identifier.issn1128-3602
dc.identifier.issue1en_US
dc.identifier.pmid36647871
dc.identifier.scopus2-s2.0-85146297804
dc.identifier.scopusqualityQ2
dc.identifier.startpage215en_US
dc.identifier.urihttps://www.europeanreview.org/article/30874
dc.identifier.urihttps://hdl.handle.net/11468/12451
dc.identifier.volume27en_US
dc.identifier.wosWOS:000925590200028
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorAyral, Muhammed
dc.institutionauthorCan, Şermin
dc.institutionauthorEsen, D.
dc.institutionauthorTopçu, İsmail
dc.institutionauthorAkıl, Ferit
dc.institutionauthorTemiz, Hakan
dc.language.isoenen_US
dc.publisherVerduci Editore s.r.len_US
dc.relation.ispartofEuropean Review for Medical and Pharmacological Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAccurate diagnosisen_US
dc.subjectArtificial intelligence applicationsen_US
dc.subjectCholesteatomaen_US
dc.subjectChronic otitis mediaen_US
dc.subjectComputed tomographyen_US
dc.titleHow advantageous is it to use computed tomography image-based artificial intelligence modelling in the differential diagnosis of chronic otitis media with and without cholesteatoma?en_US
dc.titleHow advantageous is it to use computed tomography image-based artificial intelligence modelling in the differential diagnosis of chronic otitis media with and without cholesteatoma?
dc.typeArticleen_US

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