一个人口条件变异自编码器用于fMRI分布采样和消除混杂
Anton Orlichenko1, Gang Qu1, Ziyu Zhou2
1Department of Biomedical Engineering, Tulane University, New Orleans, LA 70118.
ArXiv
|May 27, 2024
概括
这项研究介绍了DemoVAE,一个生成合成fMRI数据的模型,消除了年龄和性别等人口统计学混. 这推动了神经成像研究,为准确的预测提供了更清洁的数据.
科学领域:
- 神经成像是一种神经成像.
- 人工智能的人工智能
- 计算神经科学是一种神经科学.
背景情况:
- 来自fMRI的功能连接 (FC) 预测了各种大脑指标,但经常被人口统计学 (年龄,性别,种族) 混.
- 限制对fMRI数据集的访问限制了数据共享和研究可重复性.
研究的目的:
- 开发一个模型 (DemoVAE),从fMRI数据中消除人口混.
- 为了生成高质量的合成fMRI数据,以特定的人口特征为条件.
主要方法:
- 使用一种基于变化自编码器 (VAE) 的模型,名为DemoVAE.
- 在大型数据集上进行了训练和验证的DemoVAE:费城神经发育队列 (PNC) 和BSNIP.
- 评估了DemoVAE从人口统计学中解脱fMRI特征并生成合成数据的能力.
主要成果:
- 在fMRI数据中,DemoVAE成功地捕获了群体差异和个体变异.
- 大多数临床和认知变量,除了精神分裂症药物/症状严重程度,与DemoVAE潜伏物没有相关性.
- 与传统的VAE或GAN模型相比,生成的fMRI数据更好地代表了FC的完整分布.
结论:
- DemoVAE有效地消除了fMRI数据中的人口混,并生成高质量的合成数据.
- 基于FC的预测任务在很大程度上受到人口混的影响.
- 该模型通过减轻人口统计学偏见来促进fMRI数据的使用.
相关概念视频
Sampling Distribution
12.4K
Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
12.4K
Distributions to Estimate Population Parameter
4.1K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
4.1K
Cluster Sampling Method
11.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.9K
Confounding in Epidemiological Studies
164
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
164
Sampling Methods: Overview
309
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling.
In analytical chemistry, the choice of...
In analytical chemistry, the choice of...
309
Random Sampling Method
11.0K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
11.0K


