A Decision Support System Based on Classification Algorithms for the Diagnosis of Periodontal Disease
NCT ID: NCT06071338
Last Updated: 2023-10-06
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
250 participants
OBSERVATIONAL
2023-10-01
2024-12-30
Brief Summary
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Detailed Description
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The study purposes For periodontal applications, such as diagnosing gingivitis and periodontal disease, artificial intelligence (AI) models have been developed; however, their accuracy and technological maturity are to be evolved. The applications of such technologies in the field of periodontics are walking baby steps worldwide. The Kingdom of Saudi Arabia is moving fast in technology adoption and implementation in different sectors. However, the healthcare sector, especially clinical-related, needs original research applied to Saudi subjects. The literature in the field of machine learning applications in dentistry is limited. Although AI models for periodontology applications are still being developed, they could serve as potent diagnostic instruments. The current study was planned to add to the current gap in the literature.
Conditions
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Study Design
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OTHER
CROSS_SECTIONAL
Interventions
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Clinical Periodontal Examination
No details will be published from the clinical assessment.
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
* no periodontal treatment has been done at least 6 months prior to the enrollment
* seeking periodontal treatment
Exclusion Criteria
18 Years
ALL
Yes
Sponsors
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Ministry of Health, Saudi Arabia
OTHER_GOV
Responsible Party
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Abdulrahman Alshehri
Principal Investigator/Clinical Specialist
Principal Investigators
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Abdulrahman Al Shehri, BDS, MS
Role: PRINCIPAL_INVESTIGATOR
General Directorate of Health Affairs, Aseer Region, KSA.
Central Contacts
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References
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Ozden FO, Ozgonenel O, Ozden B, Aydogdu A. Diagnosis of periodontal diseases using different classification algorithms: a preliminary study. Niger J Clin Pract. 2015 May-Jun;18(3):416-21. doi: 10.4103/1119-3077.151785.
Alqahtani HM, Koroukian SM, Stange K, Schiltz NK, Bissada NF. Identifying Factors Associated with Periodontal Disease Using Machine Learning. J Int Soc Prev Community Dent. 2022 Dec 30;12(6):612-622. doi: 10.4103/jispcd.JISPCD_188_22. eCollection 2022 Nov-Dec.
Other Identifiers
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H-06-B-091
Identifier Type: -
Identifier Source: org_study_id
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