Accuracy of Artificial Intelligence Compared to Conventional Methods in Digital Smile Designing
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 10
- 试验地点
- 2
- 主要终点
- Accuracy
研究概览
简要总结
The study aims to assess the accuracy and patient satisfaction of smile designs based on artificial intelligence versus conventional DSD.
详细描述
Advances in digital technology are transforming dental esthetic treatments, particularly through the use of Digital Smile Design (DSD) software. These programs enable dentists to create personalized, natural-looking smile designs, improving both treatment planning and patient satisfaction. Initially, tools like PowerPoint and Photoshop were used for smile design, but modern DSD programs allow dentists to work with high-resolution 3D models to design smiles that align with facial features.
Digital smile design (DSD) technology allows dentists to create and preview new smile designs before treatment, aiding in detailed planning and clear communication with patients. This process consists of three main steps: (1) capturing digital images or videos to assess the patient's current smile, (2) analyzing these images to identify aesthetic needs, and (3) using digital tools to simulate the planned changes. Although these digital tools have greatly improved patient experience, they can be challenging to adopt in routine practice due to the required time, skill, and cost. However, this procedure could be time consuming and subjective to the dentist's skills and expertise.
To address this, artificial intelligence (AI) has been integrated into smile design software, automating tasks like facial analysis, image alignment, and smile design simulation. Accessible through apps or cloud-based platforms, AI software supports a variety of tasks, including identifying anatomical landmarks, adjusting images, and conducting live treatment simulations. DSD's integration with artificial intelligence (AI) offers further advancements, promising rapid, automated esthetic evaluations and smile designs Although AI-powered smile design tools are becoming popular in dental practices, some concerns exist that these tools may be used more for marketing purposes than for identifying genuine patient needs.
研究设计
- 研究类型
- Interventional
- 分配方式
- Non Randomized
- 干预模型
- Parallel
- 主要目的
- Diagnostic
- 盲法
- Single (Outcomes Assessor)
入排标准
- 年龄范围
- 18 Years 至 30 Years(Adult)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients with esthetic problems that require digital smile design.
- •Patient's age ranging from 19-30
- •Good oral hygiene.
- •Patients who have stable occlusion.
排除标准
- •Poor oral hygiene.
- •Patients with high caries or high plaque index.
- •Patients with periodontal problems.
- •Heavy bruxism habit or presence of any parafunctional habits.
- •Pregnant or lactating women.
- •Participating in another trial.
结局指标
主要结局
Accuracy
时间窗: immediately after the procedure
Mean difference between the two designs measured in millimeters (mm) using geomagic control software.
次要结局
- Patient satisfaction(immediately after the procedure)
研究者
Omar Osama Shaalan
Associate Professor of Conservative Dentistry
Cairo University
