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

Autor: Dan-yang LI, Yu PAN, Hui-ming ZHOU, Lei WAN, Cheng-tao LI, Mao-wen WANG, Ya-hui WANG
Jazyk: čínština
Rok vydání: 2024
Předmět:
Zdroj: Fayixue Zazhi, Vol 40, Iss 2, Pp 118-127 (2024)
Druh dokumentu: article
ISSN: 1004-5619
DOI: 10.12116/j.issn.1004-5619.2023.231103
Popis: 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.
Databáze: Directory of Open Access Journals