A Decision Support System Based on Classification Algorithms for the Diagnosis of Periodontal Disease

Study Overview
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Brief Summary
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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.

Detailed Description
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A cross-sectional study design will be applied. Two hundred fifty patients will be evaluated by an experienced periodontist and used as input variables. The final diagnosis output will be generated by considering relevant information from the patient's medical history, clinical dental examination, and radiographic exam. Of the sample of 250 patients, 20% of the participants will be assigned randomly to the test group, while the rest will be assigned to the training group before feeding it to the algorithms. 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.

Official Title
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A Decision Support System Based on Classification Algorithms for the Diagnosis of Periodontal Disease

Conditions
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Periodontal Diseases

Intervention / Treatment
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* Diagnostic Test: Clinical Periodontal Examination


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: age 18 or more no periodontal treatment has been done at least 6 months prior to the enrollment seeking periodontal treatment Exclusion Criteria: refuse to volunteer in the study

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Intervention/Treatment |
| --- |
|Diagnostic Test: Clinical Periodontal Examination|No details will be published from the clinical assessment.|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Age | <30, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75-79, >80 | One time measure; baseline during periodontal clinical examination. | 
| Gender | Male; Female. | One time measure; baseline during periodontal clinical examination. | 
| Marital statue | Married, widowed, divorced, never married | One time measure; baseline during periodontal clinical examination. | 
| Education | < secondary school, secondary school, graduate or equivalent, some college or associates degree, College graduate or higher | One time measure; baseline during periodontal clinical examination. | 
| Physical Activities | Light, Moderate, Heavy | One time measure; baseline during periodontal clinical examination. | 
| Bleeding on Probing | Yes; No | One time measure; baseline during periodontal clinical examination. | 
| Gingival Index | Percentage | One time measure; baseline during periodontal clinical examination. | 
| Plaque Index | Percentage | One time measure; baseline during periodontal clinical examination. | 
| Periodontal Probing Depth | PPD at the site of greatest loss (number) | One time measure; baseline during periodontal clinical examination. | 
| Recession Type | Yes; No | One time measure; baseline during periodontal clinical examination. | 
| Clinical Attachment Loss | CAL at the site of greatest loss (number) | One time measure; baseline during periodontal clinical examination. | 
| Radiographic Bone Loss | RBL at the site of greatest loss (percentage) | One time measure; baseline during periodontal clinical examination. | 
| Tooth Mobility | Yes; No | One time measure; baseline during periodontal clinical examination. | 
| Missing Teeth | Yes; No | One time measure; baseline during periodontal clinical examination. | 
| Furcation Involvement | Yes; No | One time measure; baseline during periodontal clinical examination. | 
| Diabetes | Healthy, <7% HbA1c, ≥7% HbA1c | One time measure; baseline during periodontal clinical examination. | 
| Smoking | None, <10 cig/day, ≥10cig/day | One time measure; baseline during periodontal clinical examination. | 
| Body Mass Index | Underweight, Healthy, Overweight, Obese | One time measure; baseline during periodontal clinical examination. | 
| Cardiovascular Disease | Yes; No | One time measure; baseline during periodontal clinical examination. | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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periodontal, disease, diagnosis, machine, learning, Saudi