痴呆症的交叉数据集评估 纵向进展 预测模型
Chen Zhang1,2,3, Lijun An1,2,3, Naren Wulan1,2,3
1Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Human brain mapping
|August 1, 2025
概括
L2C-FNN模型在各种数据集中展示了优异的阿尔茨海默病 (AD) 进展预测. 这种先进的算法显示了准确的短期和长期痴呆症预测的巨大潜力.
科学领域:
- 神经科学是一个神经科学.
- 医疗信息学 医疗信息学
- 机器学习 机器学习
背景情况:
- 准确预测阿尔茨海默病 (AD) 的进展对于临床管理至关重要.
- 2019年TADPOLE挑战评估了使用ADNI数据集预测AD的92个算法.
- TADPOLE算法对外部数据集的概括性在很大程度上仍未得到检查.
研究的目的:
- 在独立的数据集上评估顶级阿尔茨海默病预测纵向演变 (TADPOLE) 算法的概括性能.
- 为了比较五个选定的算法的预测准确度,包括TADPOLE获胜者FROG及其变体,MinimalRNN和AD-Map.
- 评估这些算法在不同患者数据可用性和预测时间范围内的稳定性.
主要方法:
- 在阿尔茨海默病神经成像计划 (ADNI) 数据集上训练了五种算法 (FROG变体,MinimalRNN,AD-Map).
- 这些模型随后在三个外部数据集上进行了测试,其中包括2312名参与者和13,200个时间点.
- FROG算法的纵向向截面 (L2C) 转换是一个关键组件,将变长纵向数据转换为固定长度特征向量.
主要成果:
- L2C-FNN模型是FROG的一个变体,在预测阿尔茨海默病进展方面表现最好.
- 在预测认知和心室体积方面,L2C-FNN和AD-Map显示了可比的最高性能.
- 在临床诊断预测方面,L2C-FNN的表现优于其他模型,并在不同数量的观察时间点和预测时间范围内保持其准确性,长达6年.
结论:
- L2C-FNN模型显示出对精确的短期和长期阿尔茨海默病进展预测有很大的潜力.
- 这些发现突显了L2C转换在处理神经退行性疾病预测复杂纵向数据方面的有效性.
- 该研究为阿尔茨海默病研究和临床应用机器学习模型的泛化提供了宝贵的见解.
更多相关视频
相关概念视频
Longitudinal Research
12.5K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
12.5K
Longitudinal Studies
248
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
248
Dementia
166
Dementia is a collective term for cognitive disorders primarily affecting memory, thinking, and reasoning. It is not a specific disease but a syndrome, with Alzheimer's disease being the most common cause, accounting for approximately 60-80% of cases. Other types include vascular dementia, Lewy body dementia, and frontotemporal dementia. Dementia affects millions worldwide, particularly older adults, though it is not a normal part of aging.
The progression of dementia is generally gradual....
The progression of dementia is generally gradual....
166
Alzheimer's Disease: Overview
669
Alzheimer's Disease (AD) is a continually advancing neurodegenerative disorder, distinguished by escalating memory loss, cognitive dysfunction, and dementia. The disease unfolds in three stages: preclinical, mild cognitive impairment (MCI), and dementia. Its onset is insidious, and the progression gradual, with the cause not well explained by other disorders.
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ...
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ...
669


