Mouth and oral disease classification using InceptionResNetV2 method

annif.suggestionsteeth|oral cancer|mouth|mouth and tooth diseases|cancerous diseases|dental diseases|deep learning|Pakistan|diagnostics|oral health|enen
annif.suggestions.linkshttp://www.yso.fi/onto/yso/p2205|http://www.yso.fi/onto/yso/p16044|http://www.yso.fi/onto/yso/p5223|http://www.yso.fi/onto/yso/p1341|http://www.yso.fi/onto/yso/p678|http://www.yso.fi/onto/yso/p274|http://www.yso.fi/onto/yso/p39324|http://www.yso.fi/onto/yso/p105965|http://www.yso.fi/onto/yso/p416|http://www.yso.fi/onto/yso/p12999en
dc.contributor.authorRashid, Javed
dc.contributor.authorQaisar, Bilal Shabbir
dc.contributor.authorFaheem, Muhammad
dc.contributor.authorAkram, Arslan
dc.contributor.authorAmin, Riaz ul
dc.contributor.authorHamid, Muhammad
dc.contributor.departmentDigital Economy-
dc.contributor.facultyfi=Tekniikan ja innovaatiojohtamisen yksikkö|en=School of Technology and Innovations|-
dc.contributor.orcidhttps://orcid.org/0000-0003-4628-4486-
dc.contributor.organizationfi=Vaasan yliopisto|en=University of Vaasa|
dc.date.accessioned2024-09-06T12:47:48Z
dc.date.accessioned2025-06-25T13:50:57Z
dc.date.available2024-09-06T12:47:48Z
dc.date.issued2024-03
dc.description.abstractDigital tools have greatly improved the detection and diagnosis of oral and dental disorders like cancer and gum disease. Lip or oral cavity cancer is more likely to develop in those with potentially malignant oral disorders. A potentially malignant disorder (PMD) and debilitating condition of the oral mucosa, oral submucous fibrosis (OSMF), can have devastating effects on one’s quality of life. Incorporating deep learning into diagnosing conditions affecting the mouth and oral cavity is challenging. Mouth and Oral Diseases Classification using InceptionResNetV2 Method was established in the current study to identify diseases such as gangivostomatitis (Gum), canker sores (CaS), cold sores (CoS), oral lichen planus (OLP), oral thrush (OT), mouth cancer (MC), and oral cancer (OC). The new collection, termed "Mouth and Oral Diseases" (MOD), comprises seven distinct categories of data. Compared to state-of-the-art approaches, the proposed InceptionResNetV2 model’s 99.51% accuracy is significantly higher.-
dc.description.notification© The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.-
dc.description.reviewstatusfi=vertaisarvioitu|en=peerReviewed|-
dc.format.bitstreamtrue
dc.format.contentfi=kokoteksti|en=fulltext|-
dc.format.extent19-
dc.format.pagerange33903–33921-
dc.identifier.olddbid21457
dc.identifier.oldhandle10024/18056
dc.identifier.urihttps://osuva.uwasa.fi/handle/11111/2853
dc.identifier.urnURN:NBN:fi-fe2024090669672-
dc.language.isoeng-
dc.publisherSpringer-
dc.relation.doi10.1007/s11042-023-16776-x-
dc.relation.funderUniversity of Vaasa (-
dc.relation.ispartofjournalMultimedia Tools and Applications-
dc.relation.issn1573-7721-
dc.relation.issn1380-7501-
dc.relation.urlhttps://doi.org/10.1007/s11042-023-16776-x-
dc.relation.volume83-
dc.rightsCC BY 4.0-
dc.source.identifierWOS:001069514100013-
dc.source.identifierScopus:85171689093-
dc.source.identifierhttps://osuva.uwasa.fi/handle/10024/18056
dc.subjectInceptionResNetV2-
dc.subjectMouth and oral diseases dataset-
dc.subjectMouth diseases-
dc.subjectOral diseases-
dc.subjectTeeth diseases-
dc.subject.disciplinefi=Tietotekniikka|en=Computer Science|-
dc.titleMouth and oral disease classification using InceptionResNetV2 method-
dc.type.okmfi=A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä|en=A1 Peer-reviewed original journal article|sv=A1 Originalartikel i en vetenskaplig tidskrift|-
dc.type.publicationarticle-
dc.type.versionpublishedVersion-

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