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

doi:10.12116/j.issn.1004-5619.2023.231103

Abstract

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

CLC Number:

Dan-yang LI, Yu PAN, Hui-ming ZHOU, Lei WAN, Cheng-tao LI, Mao-wen WANG, Ya-hui WANG. Application of Medical Statistical and Machine Learning Methods in the Age Estimation of Living Individuals[J]. Journal of Forensic Medicine, 2024, 40(2): 118-127.

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