Artificial intelligence-driven automation of nasoalveolar molding device planning: A systematic review.

IF 4.3 2区 医学 Q1 DENTISTRY, ORAL SURGERY & MEDICINE
Ahmed Yaseen Alqutaibi, Hatem Hazzaa Hamadallah, Muath Saad Alassaf, Ahmad A Othman, Ahmad A Qazali, Mohammed Ahmed Alghauli
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引用次数: 0

Abstract

Statement of problem: Despite the increasing number of publications on applying artificial intelligence (AI) in the dental field, clarity regarding the performance of different approaches for nasoalveolar molding (NAM) planning and designing is lacking. Additionally, the overall robustness of the evidence in this field remains uncertain.

Purpose: The purpose of this systematic review was to evaluate the role of AI in automating the prediction of anatomic landmarks and the design of NAM appliances.

Material and methods: A comprehensive literature search was conducted in major databases up to April 2024 without language restrictions. Studies applying AI algorithms for NAM landmark detection or appliance design were included. Data on study characteristics, AI methods, outcomes, and limitations were extracted.

Results: Six studies met the eligibility criteria. AI algorithms demonstrated high accuracy in automatically detecting landmarks and designing NAM appliances. Approaches ranged from fully automated to semi-automated workflows. Most studies reported significant time savings compared with manual methods.

Conclusions: AI applications in NAM demonstrate substantial potential in improving workflow design, as demonstrated by the high accuracy reported in various studies. The incorporation of AI in NAM planning leads to a significant reduction in treatment appointment times when compared with conventional manual methods, thereby potentially decreasing the overall duration of treatment. Nevertheless, additional research is required to foster better collaboration between dental professionals and AI experts, ultimately facilitating more efficient clinical integration.

人工智能驱动的鼻齿槽成型装置规划自动化:系统综述。
问题陈述:尽管有关将人工智能(AI)应用于牙科领域的出版物越来越多,但不同方法在鼻腔牙槽成型(NAM)规划和设计方面的性能还不够清晰。目的:本系统综述旨在评估人工智能在自动预测解剖地标和设计鼻腔成型器械方面的作用:在截至 2024 年 4 月的主要数据库中进行了全面的文献检索,没有语言限制。纳入了应用人工智能算法进行纳姆地标检测或器械设计的研究。提取了有关研究特点、人工智能方法、结果和局限性的数据:结果:六项研究符合资格标准。人工智能算法在自动检测地标和设计 NAM 器械方面表现出很高的准确性。方法从全自动到半自动工作流程不等。大多数研究报告称,与人工方法相比,人工智能大大节省了时间:人工智能在 NAM 中的应用证明了其在改进工作流程设计方面的巨大潜力,各项研究中报告的高精确度也证明了这一点。与传统的人工方法相比,将人工智能纳入 NAM 计划可显著减少治疗预约时间,从而有可能缩短总体治疗时间。不过,还需要开展更多的研究,以促进牙科专业人员与人工智能专家之间更好的合作,最终促进更高效的临床整合。
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来源期刊
Journal of Prosthetic Dentistry
Journal of Prosthetic Dentistry 医学-牙科与口腔外科
CiteScore
7.00
自引率
13.00%
发文量
599
审稿时长
69 days
期刊介绍: The Journal of Prosthetic Dentistry is the leading professional journal devoted exclusively to prosthetic and restorative dentistry. The Journal is the official publication for 24 leading U.S. international prosthodontic organizations. The monthly publication features timely, original peer-reviewed articles on the newest techniques, dental materials, and research findings. The Journal serves prosthodontists and dentists in advanced practice, and features color photos that illustrate many step-by-step procedures. The Journal of Prosthetic Dentistry is included in Index Medicus and CINAHL.
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