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

Periodontal Diseases Clinical Trial

Official title:

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

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT06071338
• Other study ID #: H-06-B-091
• Status: Not yet recruiting
• Start date: October 1, 2023
• Est. completion date: December 30, 2024

Study information

• Verified date: October 2023
• Source: Ministry of Health, Saudi Arabia
• Contact: Abdulrahman Al Shehri, BSD, MS
• Phone: +966507090251
• Email: alshehriabdulrahman3[@]gmail.com
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 250
• Est. completion date: December 30, 2024
• Est. primary completion date: December 30, 2024
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years and older

Eligibility

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

Related Conditions & MeSH terms

• Periodontal Diseases

Intervention

Diagnostic Test:
• Clinical Periodontal Examination
No details will be published from the clinical assessment.

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
Ministry of Health, Saudi Arabia

References & Publications (2)

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 — View Citation

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. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	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.
Primary	Gender	Male; Female.	One time measure; baseline during periodontal clinical examination.
Primary	Marital statue	Married, widowed, divorced, never married	One time measure; baseline during periodontal clinical examination.
Primary	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.
Primary	Physical Activities	Light, Moderate, Heavy	One time measure; baseline during periodontal clinical examination.
Primary	Bleeding on Probing	Yes; No	One time measure; baseline during periodontal clinical examination.
Primary	Gingival Index	Percentage	One time measure; baseline during periodontal clinical examination.
Primary	Plaque Index	Percentage	One time measure; baseline during periodontal clinical examination.
Primary	Periodontal Probing Depth	PPD at the site of greatest loss (number)	One time measure; baseline during periodontal clinical examination.
Primary	Recession Type	Yes; No	One time measure; baseline during periodontal clinical examination.
Primary	Clinical Attachment Loss	CAL at the site of greatest loss (number)	One time measure; baseline during periodontal clinical examination.
Primary	Radiographic Bone Loss	RBL at the site of greatest loss (percentage)	One time measure; baseline during periodontal clinical examination.
Primary	Tooth Mobility	Yes; No	One time measure; baseline during periodontal clinical examination.
Primary	Missing Teeth	Yes; No	One time measure; baseline during periodontal clinical examination.
Primary	Furcation Involvement	Yes; No	One time measure; baseline during periodontal clinical examination.
Primary	Diabetes	Healthy, <7% HbA1c,; =7% HbA1c	One time measure; baseline during periodontal clinical examination.
Primary	Smoking	None, <10 cig/day, =10cig/day	One time measure; baseline during periodontal clinical examination.
Primary	Body Mass Index	Underweight, Healthy, Overweight, Obese	One time measure; baseline during periodontal clinical examination.
Primary	Cardiovascular Disease	Yes; No	One time measure; baseline during periodontal clinical examination.