医学统计和机器学习方法在活体年龄推断中的应用

Application of Medical Statistical and Machine Learning Methods in the Age Estimation of Living Individuals

活体年龄推断研究中通常需要对大量的数据进行数理统计分析,合理的医学统计方法在数据整理和分析中发挥着重要作用,选择准确、恰当的统计方法是影响研究结果质量的关键因素之一。本文综述了活体年龄推断研究中描述性统计、差异性分析、一致性检验、多元统计分析等较为常用的医学统计方法以及浅层学习、深度学习等机器学习方法的原理和适用原则,并概括介绍了医学统计方法和机器学习方法之间的关联性和应用前景,旨在为活体年龄推断研究获得更为科学、精准的结果提供技术指引。

In the study of age estimation in living individuals,a lot of data needs to be analyzed by mathematical statistics,and reasonable medical statistical methods play an important role in data design and analysis.The selection of accurate and appropriate statistical methods is one of the key factors affecting the quality of research results.This paper reviews the principles and applicable principles of the commonly used medical statistical methods such as descriptive statistics,difference analysis,consistency test and multivariate statistical analysis,as well as machine learning methods such as shallow learning and deep learning in the age estimation research of living individuals,and summarizes the relevance and application prospects between medical statistical methods and machine learning methods.This paper aims to provide technical guidance for the age estimation research of living individuals to obtain more scientific and accurate results.