基于上颌窦的不同机器学习方法在中国西北汉族人口性别估计中的应用

IF 2.2 3区 医学 Q1 MEDICINE, LEGAL
International Journal of Legal Medicine Pub Date : 2024-09-01 Epub Date: 2024-05-18 DOI:10.1007/s00414-024-03255-7
Yu-Xin Guo, Jun-Long Lan, Yu-Xuan Song, Wen-Qin Bu, Yu Tang, Zi-Xuan Wu, Hao-Tian Meng, Di Wu, Hui Yang, Yu-Cheng Guo
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引用次数: 0

摘要

背景与目的:性别估计是法医专业知识的一个重要方面。一些特殊的解剖结构,如上颌窦,在恶劣的环境条件下仍能保持完整性,可作为性别估计的基础。由于性别估计的复杂性,已有多项研究使用不同的机器学习算法来提高根据解剖测量结果预测性别的准确性:本研究通过锥形束计算机断层扫描(CBCT)收集了中国西北地区人群上颌窦的线性数据,并利用 R 4.3.1 开发了用于性别估计的逻辑、K-近邻(KNN)、支持向量机(SVM)和随机森林(RF)模型。模型的建立和验证使用了 477 个汉族样本(75 名男性和 81 名女性,年龄在 5-17 岁之间;162 名男性和 159 名女性,年龄在 18-72 岁之间)的 CBCT 图像。测量了左右上颌窦的长度(MSL)、宽度(MSW)、高度(MSH)以及两个上颌窦之间侧壁的距离(距离)。随机抽取 80% 的数据作为训练集,其他数据作为测试集。此外,这些样本按年龄段分组,并尝试拟合模型:总体而言,测试集中 18 岁以上个体的性别估计准确率为 77.78%,其中男性的准确率为 78.12%,略高于女性的 77.42%。然而,18 岁以下个体的性别估计准确率却面临挑战。与逻辑、KNN 和 SVM 相比,RF 的准确率更高。此外,将年龄作为一个变量也提高了性别估计的准确率,尤其是在 18-27 岁年龄组,准确率提高到了 88.46%。同时,所有变量都与年龄呈线性相关:结论:上颌窦的线性测量值是对 18 岁及以上人群进行性别估计的重要工具。我们建立了一个稳健的射频模型,用于对居住在中国西北地区的汉族人口进行性别估计。如果将年龄作为预测变量,性别估计的准确性会更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Different machine learning methods based on maxillary sinus in sex estimation for northwestern Chinese Han population.

Different machine learning methods based on maxillary sinus in sex estimation for northwestern Chinese Han population.

Background & objective: Sex estimation is a critical aspect of forensic expertise. Some special anatomical structures, such as the maxillary sinus, can still maintain integrity in harsh environmental conditions and may be served as a basis for sex estimation. Due to the complex nature of sex estimation, several studies have been conducted using different machine learning algorithms to improve the accuracy of sex prediction from anatomical measurements.

Material & methods: In this study, linear data of the maxillary sinus in the population of northwest China by using Cone-Beam Computed Tomography (CBCT) were collected and utilized to develop logistic, K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and random forest (RF) models for sex estimation with R 4.3.1. CBCT images from 477 samples of Han population (75 males and 81 females, aged 5-17 years; 162 males and 159 females, aged 18-72) were used to establish and verify the model. Length (MSL), width (MSW), height (MSH) of both the left and right maxillary sinuses and distance of lateral wall between two maxillary sinuses (distance) were measured. 80% of the data were randomly picked as the training set and others were testing set. Besides, these samples were grouped by age bracket and fitted models as an attempt.

Results: Overall, the accuracy of the sex estimation for individuals over 18 years old on the testing set was 77.78%, with a slightly higher accuracy rate for males at 78.12% compared to females at 77.42%. However, accuracy of sex estimation for individuals under 18 was challenging. In comparison to logistic, KNN and SVM, RF exhibited higher accuracy rates. Moreover, incorporating age as a variable improved the accuracy of sex estimation, particularly in the 18-27 age group, where the accuracy rate increased to 88.46%. Meanwhile, all variables showed a linear correlation with age.

Conclusion: The linear measurements of the maxillary sinus could be a valuable tool for sex estimation in individuals aged 18 and over. A robust RF model has been developed for sex estimation within the Han population residing in the northwestern region of China. The accuracy of sex estimation could be higher when age is used as a predictive variable.

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来源期刊
CiteScore
5.80
自引率
9.50%
发文量
165
审稿时长
1 months
期刊介绍: The International Journal of Legal Medicine aims to improve the scientific resources used in the elucidation of crime and related forensic applications at a high level of evidential proof. The journal offers review articles tracing development in specific areas, with up-to-date analysis; original articles discussing significant recent research results; case reports describing interesting and exceptional examples; population data; letters to the editors; and technical notes, which appear in a section originally created for rapid publication of data in the dynamic field of DNA analysis.
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