Development and Validation of an AI-Powered Mobile Application (ChkUrSmle) for Orthodontic Treatment Need Assessment Using Intraoral Photographs
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 1,000
- 试验地点
- 1
- 主要终点
- 1.Developing an AI-driven system for automated orthodontic assessment.
研究概览
简要总结
SUMMARY:
Rationale and Background:
Orthodontic malocclusions, if untreated, can lead to significant oral health issues, including speech difficulties, chewing impairments, and periodontal diseases. In underserved regions, limited access to orthodontic care exacerbates these issues, leaving many individuals without timely diagnosis or treatment. With the growing capabilities of artificial intelligence (AI), automated assessment offers a promising solution to enhance accessibility and efficiency in orthodontic diagnostics.
Novelty:
This study introduces a novel AI-powered mobile application for orthodontic treatment need assessment using intraoral photographs. By automating the Index of Orthodontic Treatment Need (IOTN) scoring, the app provides standardized and objective evaluations. Unlike traditional manual assessments that require in-person visits, this AI-based tool enables remote, cost-effective, and rapid diagnosis, making orthodontic care more accessible, particularly in resource-limited areas.
Objective:
The study aims to develop and validate an AI-based system for automated IOTN scoring by comparing it with manual assessments by orthodontic specialists.
Methods:
This cross-sectional study will include 1,000 participants aged 10–18 years from Ranjeet Deshmukh Dental College, Nagpur. Intraoral photographs will be analyzed by both the AI system and orthodontic experts. Statistical validation using Kappa statistics and Spearman correlation will measure the agreement and accuracy between AI and manual evaluations.
Expected Outcome:
The study aims to demonstrate that AI can deliver reliable and standardized orthodontic assessments, improving access to early diagnosis and treatment. This innovation has the potential to enhance oral healthcare equity, especially in remote and underserved areas.
研究设计
- 研究类型
- Interventional
- 分配方式
- Not Applicable
- 盲法
- Not Applicable
入排标准
- 年龄范围
- 10.00 Year(s) 至 18.00 Year(s)（—）
- 性别
- All
入选标准
- •1.Oral assent from subjects and written consent from parents/Guardian willing to participate in the study.
- •2.Participants aged between 10 and 18 years.
- •3.Availability of intraoral photographs taken as part of the study.
- •4.No prior orthodontic treatment (such as braces or aligners).
- •5.Ability to follow simple instructions for capturing intraoral photographs.
- •6.Participants willing to participate in the study.
排除标准
- •1.Participants with a history of significant dental trauma.
- •2.Individuals who have already undergone orthodontic treatment.
- •3.Participants who are unable to provide consent or have not received parental consent (for minors).
- •4.Presence of active oral infections or severe dental caries that could interfere with the assessment.
结局指标
主要结局
1.Developing an AI-driven system for automated orthodontic assessment.
时间窗: 12 Months
2.Validating the accuracy and reliability of AI-based IOTN scoring by comparing it with manual evaluations by orthodontic specialists.
时间窗: 12 Months
3.Enhancing accessibility to orthodontic diagnostics by providing a non-invasive, remote, and cost-effective assessment tool.
时间窗: 12 Months
次要结局
未报告次要终点