计算机与数字工程2024，Vol.52Issue(2)：321-326,331,7.DOI:10.3969/j.issn.1672-9722.2024.02.004
基于人群特征的阿尔兹海默症分类方法
Classification Method of Alzheimer's Disease Based on Population Characteristics
摘要
Abstract
In Alzheimer's disease(Alzheimer's disease,AD)classification research,data sets such as images and biomarkers contain few samples and high acquisition costs.To cope with this problem,the paper proposes a method of modeling based on popu-lation characteristics,and conducts experiments on the CMDS data set.First,the PAR method is used to analyze the correlation be-tween features and AD,and select features based on the analysis results.Then,the ADASYN algorithm is used to solve the problem of unbalanced training set samples.Finally,the XGBoost algorithm for training is used to obtain the final model.The accuracy and recall rates of the model reached 79.5%and 77.6%,and the AUC reached 0.83.The experimental results prove the effectiveness of this method.关键词
阿尔兹海默症/人群特征/ADASYN/PAR/机器学习Key words
Alzheimer's disease/population characteristics/ADASYN/PAR/machine learning分类
信息技术与安全科学引用本文复制引用
胡建举,张晓龙,曾燕,胡斐斐..基于人群特征的阿尔兹海默症分类方法[J].计算机与数字工程,2024,52(2):321-326,331,7.基金项目
科技部重大项目(编号:2020AAA08600) （编号:2020AAA08600）
国家重点研发计划(编号:2020YFC2006000)资助. （编号:2020YFC2006000）
