Deep-learning-based mandibular third molar recognition and classification system

Deep-learning-based mandibular third molar recognition and classification system | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Deep-learning-based mandibular third molar recognition and classification system Xin Huang, Qinruo Zhang, Aosen Liang, Yajing Zhang, Jianing Li, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8109905/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 16 You are reading this latest preprint version Abstract Background: Traditional impacted-tooth classification methods are limited, as they rely heavily on clinicians' subjective judgment and often exhibit poor consistency. To enhance diagnostic accuracy, provide clinical utility, and develop a scalable, intelligent decision-support system for oral and maxillofacial surgery, this study proposes an objective and quantitative approach that integrates deep learning-based image segmentation with geometric feature quantification for classifying mandibular third molar impaction types. Methods: A decoupled segmentation-classification workflow was implemented, utilizing a fusion model that integrates U-Net, U-Net++, and DeepLabV3+ for tooth contour segmentation. Results: The fusion model achieved superior performance, with an accuracy of 0.937 and sensitivity of 0.889 for third molar segmentation. Classification based on the α-angle, defined as the angle between the long axis of the third molar and the reference line of adjacent teeth, reached an overall accuracy of 96.2%. Distoangular impaction demonstrated the highest specificity (0.983), highlighting the reliability of the system. Conclusions: The combination of multimodel segmentation techniques and a newly defined angle criterion significantly improves classification accuracy, offering an efficient and quantifiable tool for clinical practice. This approach reduces diagnostic subjectivity, leverages the advantages of panoramic radiography, and demonstrates strong potential for advancing intelligent dentistry. Future studies will focus on model optimization to accommodate diverse imaging data and further advance clinical applications in oral and maxillofacial surgery. Impacted tooth classification Deep learning Panoramic radiograph Geometric angle measurement Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 24 Apr, 2026 Reviews received at journal 25 Jan, 2026 Reviews received at journal 16 Jan, 2026 Reviews received at journal 29 Dec, 2025 Reviews received at journal 28 Dec, 2025 Reviews received at journal 16 Dec, 2025 Reviewers agreed at journal 08 Dec, 2025 Reviewers agreed at journal 04 Dec, 2025 Reviewers agreed at journal 03 Dec, 2025 Reviewers agreed at journal 03 Dec, 2025 Reviewers agreed at journal 03 Dec, 2025 Reviewers invited by journal 02 Dec, 2025 Editor invited by journal 18 Nov, 2025 Editor assigned by journal 14 Nov, 2025 Submission checks completed at journal 14 Nov, 2025 First submitted to journal 13 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8109905","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":554701372,"identity":"cd39f83d-8553-4196-9a89-869409d735f0","order_by":0,"name":"Xin Huang","email":"","orcid":"","institution":"School and Hospital of Stomatology, Tianjin Medical University, No.12 Qixiangtai Road, Heping District, Tianjin 300070, PR China","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Huang","suffix":""},{"id":554701373,"identity":"2c85ca49-b05c-4050-b1d7-238618b9a5af","order_by":1,"name":"Qinruo Zhang","email":"","orcid":"","institution":"School and Hospital of Stomatology, Tianjin Medical University, No.12 Qixiangtai Road, Heping District, Tianjin 300070, PR China","correspondingAuthor":false,"prefix":"","firstName":"Qinruo","middleName":"","lastName":"Zhang","suffix":""},{"id":554701374,"identity":"b53247c9-a932-4a0c-8d85-3cb39e1ad090","order_by":2,"name":"Aosen Liang","email":"","orcid":"","institution":"School and Hospital of Stomatology, Tianjin Medical University, No.12 Qixiangtai Road, Heping District, Tianjin 300070, PR China","correspondingAuthor":false,"prefix":"","firstName":"Aosen","middleName":"","lastName":"Liang","suffix":""},{"id":554701375,"identity":"577fcb14-be54-4354-8961-17d0e2f5240c","order_by":3,"name":"Yajing Zhang","email":"","orcid":"","institution":"School and Hospital of Stomatology, Tianjin Medical University, No.12 Qixiangtai Road, Heping District, Tianjin 300070, PR China","correspondingAuthor":false,"prefix":"","firstName":"Yajing","middleName":"","lastName":"Zhang","suffix":""},{"id":554701376,"identity":"09b04ac4-5a59-4300-a91b-4bfb271ae9c7","order_by":4,"name":"Jianing Li","email":"","orcid":"","institution":"School and Hospital of Stomatology, Tianjin Medical University, No.12 Qixiangtai Road, Heping District, Tianjin 300070, PR China","correspondingAuthor":false,"prefix":"","firstName":"Jianing","middleName":"","lastName":"Li","suffix":""},{"id":554701377,"identity":"31b60d5a-bc9c-46c6-98cb-e58ca8a991d7","order_by":5,"name":"Fengyan Li","email":"","orcid":"","institution":"School and Hospital of Stomatology, Tianjin Medical University, No.12 Qixiangtai Road, Heping District, Tianjin 300070, PR China","correspondingAuthor":false,"prefix":"","firstName":"Fengyan","middleName":"","lastName":"Li","suffix":""},{"id":554701378,"identity":"c1bb4a59-5f9d-4772-b68f-8b9335946b89","order_by":6,"name":"Yuheng Wang","email":"","orcid":"","institution":"School and Hospital of Stomatology, Tianjin Medical University, No.12 Qixiangtai Road, Heping District, Tianjin 300070, PR China","correspondingAuthor":false,"prefix":"","firstName":"Yuheng","middleName":"","lastName":"Wang","suffix":""},{"id":554701379,"identity":"1df72f68-2168-429b-911b-1b391a9fae77","order_by":7,"name":"Yuxuan Fan","email":"","orcid":"","institution":"School and Hospital of Stomatology, Tianjin Medical University, No.12 Qixiangtai Road, Heping District, Tianjin 300070, PR China","correspondingAuthor":false,"prefix":"","firstName":"Yuxuan","middleName":"","lastName":"Fan","suffix":""},{"id":554701380,"identity":"13812aa8-9d70-4cdf-86c8-873d5b18aece","order_by":8,"name":"Jianmin Han","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArUlEQVRIiWNgGAWjYBACAzCugHAkSNByxoBELQyMbaRoMWc/e6Do5rw/0QYHmA/e5mGwyyOoxbInL8E4d5tB7oYDbMnWPAzJxYQddiDHAKqFx0yah+FAYgNBLeffALXMAWnh/0aklhsgWxrAtrARqwVoS84x49yZh9mMLecYJBPjsBwz45waudy+480Pb7ypsCOsBQjYIJHCDDaBCPUgtQ+IUzcKRsEoGAUjFgAAR2w6tQD++J0AAAAASUVORK5CYII=","orcid":"","institution":"School and Hospital of Stomatology, Tianjin Medical University, No.12 Qixiangtai Road, Heping District, Tianjin 300070, PR China","correspondingAuthor":true,"prefix":"","firstName":"Jianmin","middleName":"","lastName":"Han","suffix":""}],"badges":[],"createdAt":"2025-11-14 02:38:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8109905/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8109905/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97667613,"identity":"107505b0-3c8a-416f-be65-5d22e1b857c2","added_by":"auto","created_at":"2025-12-08 09:23:55","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":139715,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/780962c76653d4b4f43ffb9d.docx"},{"id":97668575,"identity":"361b8a78-7134-4252-ad90-67f2fd2dca6a","added_by":"auto","created_at":"2025-12-08 09:25:48","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":51054,"visible":true,"origin":"","legend":"","description":"","filename":"fileM3SegClass.docx","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/c4a056e0bf2f49a1673d5f70.docx"},{"id":97668591,"identity":"e6b596d1-9e1d-4ef2-ad2b-a032685ce9cd","added_by":"auto","created_at":"2025-12-08 09:25:50","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":12371506,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/816c5de374f5d2505446432f.docx"},{"id":97450354,"identity":"07511a74-2f11-4f25-9eaf-9698601b7c23","added_by":"auto","created_at":"2025-12-04 13:34:15","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":20137,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/5522e0dad868b9b78ccb3db9.docx"},{"id":97669098,"identity":"5a88efac-a576-4ad1-aabe-633599681e96","added_by":"auto","created_at":"2025-12-08 09:27:12","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":557361,"visible":true,"origin":"","legend":"","description":"","filename":"Figure3.docx","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/69ed26dd9ec9940f29aee2a4.docx"},{"id":97450356,"identity":"996ebd67-48e4-44e1-a8a6-bb39e1397aa6","added_by":"auto","created_at":"2025-12-04 13:34:15","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":16983,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/ca45b9270110a7edbe3b8141.docx"},{"id":97669294,"identity":"10e7f801-6a26-4628-aed2-8765362e5352","added_by":"auto","created_at":"2025-12-08 09:27:46","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":372147,"visible":true,"origin":"","legend":"","description":"","filename":"Figure4.docx","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/ebe05034c409168576c96f87.docx"},{"id":97450361,"identity":"d00ac7da-cd4f-4a9e-a46f-3532c0b7e298","added_by":"auto","created_at":"2025-12-04 13:34:16","extension":"json","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11039,"visible":true,"origin":"","legend":"","description":"","filename":"e32be25e0ca040f098f52fd7d7832e84.json","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/3fb091286e3ac1bd7718a145.json"},{"id":97450368,"identity":"72ba16ef-4a38-4dc7-b35c-9de3fb144192","added_by":"auto","created_at":"2025-12-04 13:34:16","extension":"xml","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":128766,"visible":true,"origin":"","legend":"","description":"","filename":"e32be25e0ca040f098f52fd7d7832e841enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/fcc1d0c2e1a7e618c93a4b4f.xml"},{"id":97450364,"identity":"b9e6c43f-aee2-49e3-a786-7c85dc90b22c","added_by":"auto","created_at":"2025-12-04 13:34:16","extension":"jpeg","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":430605,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/a22f313061ab261fb7e74684.jpeg"},{"id":97669048,"identity":"3494d3df-c8a5-437a-b8b8-fef0d2ce18e1","added_by":"auto","created_at":"2025-12-08 09:27:09","extension":"jpeg","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":901730,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/f89b18d13ecaa2712c7fdb45.jpeg"},{"id":97450357,"identity":"93905632-9b93-42e2-b3a1-ede15585560c","added_by":"auto","created_at":"2025-12-04 13:34:16","extension":"jpeg","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1030137,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/d8589bbef81818c41bb1f106.jpeg"},{"id":97669292,"identity":"72d85e40-14b3-4797-99b7-fb36a32d8d41","added_by":"auto","created_at":"2025-12-08 09:27:46","extension":"jpeg","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":471449,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/2eebae58f978c1b07f63e9b6.jpeg"},{"id":97667543,"identity":"8e4f2232-e2b4-4120-8307-982a8a08cc36","added_by":"auto","created_at":"2025-12-08 09:23:45","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":75854,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/d64073cac8d1c45cac50de40.png"},{"id":97668104,"identity":"17f321bf-19fd-4b47-aa5a-7abeed78ff73","added_by":"auto","created_at":"2025-12-08 09:24:50","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":232597,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/bce8302840f82f3c6f432a29.png"},{"id":97450366,"identity":"c64ac326-02f9-4415-8f7d-7489a5a928fb","added_by":"auto","created_at":"2025-12-04 13:34:16","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":221734,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/ae398416ec0534d5e093ac26.png"},{"id":97450370,"identity":"717d3b6f-bbc6-468a-98e9-2c34e4a967fe","added_by":"auto","created_at":"2025-12-04 13:34:16","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":95329,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/e69bc3c77c3404108cbe7205.png"},{"id":97450371,"identity":"b76ae049-b10b-46e3-a7ed-f9cdd2067fd6","added_by":"auto","created_at":"2025-12-04 13:34:16","extension":"xml","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":126876,"visible":true,"origin":"","legend":"","description":"","filename":"e32be25e0ca040f098f52fd7d7832e841structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/4815610df8c2c208be9a09e5.xml"},{"id":97450369,"identity":"e1a80c01-afea-4b87-b0e6-b114af89a4e8","added_by":"auto","created_at":"2025-12-04 13:34:16","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":139140,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1/948e3ddbf72a795d700405cd.html"},{"id":97677631,"identity":"84672fc7-96c0-409d-b3bf-1b0688c0cbee","added_by":"auto","created_at":"2025-12-08 09:53:47","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2277684,"visible":true,"origin":"","legend":"","description":"","filename":"fileM3SegClass1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8109905/v1_covered_26945336-556a-4cd1-a66a-f345d072c47a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Deep-learning-based mandibular third molar recognition and classification system","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Impacted tooth classification, Deep learning, Panoramic radiograph, Geometric angle measurement","lastPublishedDoi":"10.21203/rs.3.rs-8109905/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8109905/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eTraditional impacted-tooth classification methods are limited, as they rely heavily on clinicians' subjective judgment and often exhibit poor consistency. To enhance diagnostic accuracy, provide clinical utility, and develop a scalable, intelligent decision-support system for oral and maxillofacial surgery, this study proposes an objective and quantitative approach that integrates deep learning-based image segmentation with geometric feature quantification for classifying mandibular third molar impaction types.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA decoupled segmentation-classification workflow was implemented, utilizing a fusion model that integrates U-Net, U-Net++, and DeepLabV3+ for tooth contour segmentation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe fusion model achieved superior performance, with an accuracy of 0.937 and sensitivity of 0.889 for third molar segmentation. Classification based on the α-angle, defined as the angle between the long axis of the third molar and the reference line of adjacent teeth, reached an overall accuracy of 96.2%. Distoangular impaction demonstrated the highest specificity (0.983), highlighting the reliability of the system.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThe combination of multimodel segmentation techniques and a newly defined angle criterion significantly improves classification accuracy, offering an efficient and quantifiable tool for clinical practice. This approach reduces diagnostic subjectivity, leverages the advantages of panoramic radiography, and demonstrates strong potential for advancing intelligent dentistry. Future studies will focus on model optimization to accommodate diverse imaging data and further advance clinical applications in oral and maxillofacial surgery.\u003c/p\u003e","manuscriptTitle":"Deep-learning-based mandibular third molar recognition and classification system","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-04 13:34:11","doi":"10.21203/rs.3.rs-8109905/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-24T14:06:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-25T14:45:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-16T16:56:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-29T08:35:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-28T19:30:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-16T14:16:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"133166353511539145904120487770108716874","date":"2025-12-08T09:49:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"202168632010823657365511727803352923483","date":"2025-12-04T08:28:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"86553461686073473967023494538185390060","date":"2025-12-03T12:10:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"10130630659974121373973043114132984094","date":"2025-12-03T06:39:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"45615345080127816470258268765928944673","date":"2025-12-03T06:06:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-02T22:53:31+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-18T09:22:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-14T08:48:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-14T08:47:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Oral Health","date":"2025-11-14T02:34:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"361f3d93-3c97-48e0-8699-3672eb92c265","owner":[],"postedDate":"December 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T12:08:50+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-04 13:34:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8109905","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8109905","identity":"rs-8109905","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}