Dynamic Survival Prediction Using Sparse Longitudinal Images via Multi-Dimensional Functional Principal Component Analysis

IF 1.4 2区数学 Q2 STATISTICS & PROBABILITY

Journal of Computational and Graphical Statistics Pub Date : 2024-05-23 DOI:10.1080/10618600.2024.2335182

Haolun Shi, Shu Jiang, Da Ma, Mirza Faisal Beg, Jiguo Cao

引用次数: 0

Abstract

Our work is motivated by predicting the progression of Alzheimer’s disease (AD) based on a series of longitudinally observed brain scan images. Existing works on dynamic prediction for AD focus pri...

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通过多维功能主成分分析利用稀疏纵向图像进行动态生存预测

我们的工作是基于一系列纵向观察的大脑扫描图像来预测阿尔茨海默病（AD）的进展。现有的阿兹海默病动态预测工作主要集中在对阿兹海默病进展的预测上。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Computational and Graphical Statistics 数学-统计学与概率论

CiteScore

3.50

自引率

8.30%

发文量

153

审稿时长

>12 weeks

期刊介绍： The Journal of Computational and Graphical Statistics (JCGS) presents the very latest techniques on improving and extending the use of computational and graphical methods in statistics and data analysis. Established in 1992, this journal contains cutting-edge research, data, surveys, and more on numerical graphical displays and methods, and perception. Articles are written for readers who have a strong background in statistics but are not necessarily experts in computing. Published in March, June, September, and December.