官方服务：
资源简介：
Alzheimer 3 Classes Brain MRI
阿尔茨海默病三类脑部磁共振成像（Brain MRI）数据集
应用场景：
创建时间：
2026-06-26
相关数据集
ADMC dataset
该数据集是一个专为阿尔茨海默病分类构建的私有数据集，包含了来自100名受试者的脑电图(EEG)、磁共振成像(MRI)以及量表数据。数据集中还包含了人口统计学细节：平均年龄为72.4岁，年龄范围从56岁至93岁，其中女性56名，已婚人士22名。该数据集被划分为80个样本用于训练，以及20个样本用于评估。规模上，共有100名受试者参与，任务是对阿尔茨海默病、轻度认知障碍和正常认知进行分类。
arXiv1070
Summary of classification reports of CN versus AD subjects based on structural MRI data from different groups.
MLM = Machine Learning Method; SS = Sample size; NM = Normalization Method; CV = Cross-validation,*-Images were downsampled.
Figshare2015-12-02 更新50
Table_1_Morphological, Structural, and Functional Networks Highlight the Role of the Cortical-Subcortical Circuit in Individuals With Subjective Cognitive Decline.docx
Subjective cognitive decline (SCD) is considered the earliest stage of the clinical manifestations of the continuous progression of Alzheimer’s Disease (AD). Previous studies have suggested that multi
NIAID Data Ecosystem30
Table8_Development and validation of immune-based biomarkers and deep learning models for Alzheimer’s disease.XLSX
Background: Alzheimer’s disease (AD) is the most common form of dementia in old age and poses a severe threat to the health and life of the elderly. However, traditional diagnostic methods and the ATN
NIAID Data Ecosystem100
Amyloid and cerebrovascular burden divergently influence brain functional network changes over time
Objective: To examine the effects of baseline Alzheimer’s disease and cerebrovascular disease markers on longitudinal default mode network (DMN) and executive control network (ECN) functional connecti
NIAID Data Ecosystem40
