A Decision Support System Based on Classification Algorithms for the Diagnosis of Periodontal Disease
Study Details
Study Description
Brief Summary
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.
Condition or Disease | Intervention/Treatment | Phase |
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Detailed Description
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.
Study Design
Outcome Measures
Primary Outcome Measures
- Age [One time measure; baseline during periodontal clinical examination.]
<30, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75-79, >80
- Gender [One time measure; baseline during periodontal clinical examination.]
Male; Female.
- Marital statue [One time measure; baseline during periodontal clinical examination.]
Married, widowed, divorced, never married
- Education [One time measure; baseline during periodontal clinical examination.]
< secondary school, secondary school, graduate or equivalent, some college or associates degree, College graduate or higher
- Physical Activities [One time measure; baseline during periodontal clinical examination.]
Light, Moderate, Heavy
- Bleeding on Probing [One time measure; baseline during periodontal clinical examination.]
Yes; No
- Gingival Index [One time measure; baseline during periodontal clinical examination.]
Percentage
- Plaque Index [One time measure; baseline during periodontal clinical examination.]
Percentage
- Periodontal Probing Depth [One time measure; baseline during periodontal clinical examination.]
PPD at the site of greatest loss (number)
- Recession Type [One time measure; baseline during periodontal clinical examination.]
Yes; No
- Clinical Attachment Loss [One time measure; baseline during periodontal clinical examination.]
CAL at the site of greatest loss (number)
- Radiographic Bone Loss [One time measure; baseline during periodontal clinical examination.]
RBL at the site of greatest loss (percentage)
- Tooth Mobility [One time measure; baseline during periodontal clinical examination.]
Yes; No
- Missing Teeth [One time measure; baseline during periodontal clinical examination.]
Yes; No
- Furcation Involvement [One time measure; baseline during periodontal clinical examination.]
Yes; No
- Diabetes [One time measure; baseline during periodontal clinical examination.]
Healthy, <7% HbA1c, ≥7% HbA1c
- Smoking [One time measure; baseline during periodontal clinical examination.]
None, <10 cig/day, ≥10cig/day
- Body Mass Index [One time measure; baseline during periodontal clinical examination.]
Underweight, Healthy, Overweight, Obese
- Cardiovascular Disease [One time measure; baseline during periodontal clinical examination.]
Yes; No
Eligibility Criteria
Criteria
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
Contacts and Locations
Locations
No locations specified.Sponsors and Collaborators
- Ministry of Health, Saudi Arabia
Investigators
- Principal Investigator: Abdulrahman Al Shehri, BDS, MS, General Directorate of Health Affairs, Aseer Region, KSA.
Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- H-06-B-091