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

Ministry of Health, Saudi Arabia

Status: Not yet enrolling

Conditions: Periodontal Diseases

Treatments: Diagnostic Test: Clinical Periodontal Examination

Study type: Observational

Funder types: Other

Identifiers

NCT06071338

H-06-B-091

Details and patient eligibility

About

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.

Full 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.

Enrollment: 250 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: Accepts Healthy Volunteers

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