法医学杂志 ›› 2024, Vol. 40 ›› Issue (2): 118-127.DOI: 10.12116/j.issn.1004-5619.2023.231103

• 法医人类学年龄推断专题 • 上一篇    

医学统计和机器学习方法在活体年龄推断中的应用

李丹阳1,2,3,4(), 潘宇5(), 周慧明1,4, 万雷1, 李成涛1, 汪茂文1, 王亚辉1()   

  1. 1.司法鉴定科学研究院 上海市法医学重点实验室 司法部司法鉴定重点实验室 上海市司法鉴定专业技术服务平台,上海 200063
    2.山西医科大学医学科学院,山西 太原 030000
    3.山西医科大学公共卫生学院,山西 太原 030000
    4.山西医科大学法医学院,山西 晋中 030600
    5.上海市浦东新区公利医院司法鉴定所,上海 210035
  • 收稿日期:2023-11-25 发布日期:2024-05-21 出版日期:2024-04-25
  • 通讯作者: 王亚辉
  • 作者简介:李丹阳(1999—),女,硕士研究生,主要从事法医临床学和法医人类学研究;E-mail:lidanyang19990304@163.com
    潘宇(1986—),男,主要从事法医临床学研究和鉴定;E-mail:55470623@qq.com
    第一联系人:李丹阳和潘宇为共同第一作者
  • 基金资助:
    国家重点研发计划资助项目(2022YFC3302004);国家自然科学基金资助项目(81571859);上海市2019年度“科技创新行动计划”技术标准项目(19DZ2201300);上海市法医学重点实验室资助项目(21DZ2270800);上海市司法鉴定专业技术服务平台资助项目;司法部司法鉴定重点实验室资助项目

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

Dan-yang LI1,2,3,4(), Yu PAN5(), Hui-ming ZHOU1,4, Lei WAN1, Cheng-tao LI1, Mao-wen WANG1, Ya-hui WANG1()   

  1. 1.Shanghai Key Laboratory of Forensic Medicine, Key Laboratory of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, China
    2.Academy of Medical Sciences, Shanxi Medical University, Taiyuan 030000, China
    3.School of Public Health, Shanxi Medical University, Taiyuan 030000, China
    4.School of Forensic Medicine, Shanxi Medical University, Jinzhong 030600, Shanxi Province, China
    5.Forensic Institute of Shanghai Pudong New Area Gongli Hospital, Shanghai 210035
  • Received:2023-11-25 Online:2024-05-21 Published:2024-04-25
  • Contact: Ya-hui WANG

摘要:

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。

关键词: 法医人类学, 医学统计学, 机器学习, 年龄推断, 骨龄, 牙龄, 综述

Abstract:

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.

Key words: forensic anthropology, medical statistics, machine learning, age estimation, skeletal age, dental age, review

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