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人工智能在全景片上进行年龄推断方法的有效性——系统综述。

Efficacy of the methods of age determination using artificial intelligence in panoramic radiographs - a systematic review.

机构信息

Research center of the Institute National of Legal Medicine and Forensic Sciences, Research Institute, Faculty of Medicine, University of Antioquia, Medellin, Colombia.

Institute National of Legal Medicine and Forensic Sciences, Medellin, Colombia.

出版信息

Int J Legal Med. 2024 Jul;138(4):1459-1496. doi: 10.1007/s00414-024-03162-x. Epub 2024 Feb 24.

Abstract

The aim of this systematic review is to analyze the literature to determine whether the methods of artificial intelligence are effective in determining age in panoramic radiographs. Searches without language and year limits were conducted in PubMed/Medline, Embase, Web of Science, and Scopus databases. Hand searches were also performed, and unpublished manuscripts were searched in specialized journals. Thirty-six articles were included in the analysis. Significant differences in terms of root mean square error and mean absolute error were found between manual methods and artificial intelligence techniques, favoring the use of artificial intelligence (p < 0.00001). Few articles compared deep learning methods with machine learning models or manual models. Although there are advantages of machine learning in data processing and deep learning in data collection and analysis, non-comparable data was a limitation of this study. More information is needed on the comparison of these techniques, with particular emphasis on time as a variable.

摘要

本系统评价的目的是分析文献,以确定人工智能方法在确定全景片年龄方面是否有效。在 PubMed/Medline、Embase、Web of Science 和 Scopus 数据库中进行了无语言和年限限制的检索。还进行了手工检索,并在专业期刊中搜索了未发表的手稿。有 36 篇文章被纳入分析。手动方法和人工智能技术之间在均方根误差和平均绝对误差方面存在显著差异,这有利于人工智能的使用(p<0.00001)。很少有文章将深度学习方法与机器学习模型或手动模型进行比较。尽管机器学习在数据处理方面有优势,深度学习在数据收集和分析方面有优势,但不可比的数据是本研究的一个局限性。需要更多关于这些技术比较的信息,特别强调时间作为一个变量。

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