Assessment of Decision Support System Software in Extraction and Anchorage Planning Among Adult Patients Using Computer Algorithm

Cairo University80 enrolled

Overview

It was introduced in dentistry to be used in innovative research and development in addition to facilitating the decision in complicated cases and ensure high patient care quality. In the field of Orthodontics in specific, many studies previously mentioned the idea of artificial intelligence showing very promising results and high degree of reliability. It was used in different domains in orthodontics like diagnosis, treatment planning, evaluation of treatment outcome

In this study, the aim is to access the efficiency of the new decision support system in determining whether the decision is extraction or non-extraction and the anchorage plan required for each case. This was performed in the past in many countries and those studies are published

Study Type

OBSERVATIONAL

Enrollment

Conditions

Cases That Need Extraction of Teeth in Orthodontics Anchorage Planning

Interventions

Well finished cases

Eligibility

Sex: ALLMin age: 15 YearsMax age: 35 Years

Medical Language ↔ Plain English

Inclusion Criteria: 1. Cases with well finished orthodontic treatment. 2. Cases with history of crowding more than 10 mm and requiring extraction. 3. Cases with no severe skeletal discrepancy. 4. Well documented cases with both pre-operative and post-operative records. 5. Patients with a full set of permanent teeth erupted Exclusion Criteria: 1. Improperly finished orthodontic cases. 2. Cases with mild crowding managed by treatment options other than extraction. 3. Growing patients or showing any residual growth remaining in cephalometric analysis 4. Cases with severe skeletal discrepancy. 5. Poorly documented cases. 6. Patients not sticking to anchorage plan

Outcomes

Primary Outcomes

To study the efficiency of the program decisions in terms of extraction/non-extraction and Anchorage planning decisions

The concordance correlation coefficient would be used to measure the agreement between the 2 methods on the basis of the values (%) assigned for each treatment option by the 2 methods (quantitative data).

Time frame: 1 year