Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Alzheimer's Disease: Overview01:26

Alzheimer's Disease: Overview

494
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...
494
Alzheimer's Disease: Treatment01:22

Alzheimer's Disease: Treatment

195
Alzheimer's Disease (AD), a neurodegenerative disorder, is pathologically identified by amyloid plaques and neurofibrillary tangles composed of tau protein. AD pharmacotherapy aims to manage cognitive symptoms, delay disease progression, and treat behavioral symptoms. The treatment is primarily symptomatic and palliative, with no definitive disease-modifying therapy available. Cholinesterase inhibitors, including donepezil (Aricept), rivastigmine (Exelon), and galantamine (Razadyne), are...
195
Dementia01:30

Dementia

115
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....
115

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Capturing Requirements for a Data Annotation Tool for Intensive Care: Experimental User-Centered Design Study.

JMIR human factors·2025
Same author

Beyond Expected Patterns in Insulin Needs of People With Type 1 Diabetes: Temporal Analysis of Automated Insulin Delivery Data.

JMIRx med·2024
Same author

Estimating Information Theoretic Measures via Multidimensional Gaussianization.

IEEE transactions on pattern analysis and machine intelligence·2024
Same author

Explainable hierarchical clustering for patient subtyping and risk prediction.

Experimental biology and medicine (Maywood, N.J.)·2023
Same author

Design and Evaluation of an Intensive Care Unit Dashboard Built in Response to the COVID-19 Pandemic: Semistructured Interview Study.

JMIR human factors·2023
Same author

Image Statistics Predict the Sensitivity of Perceptual Quality Metrics.

ArXiv·2023

相关实验视频

Updated: Jul 9, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.1K

一个强大的基于类分解的方法来检测阿尔茨海默病的进展.

Maha M Alwuthaynani1,2, Zahraa S Abdallah1, Raul Santos-Rodriguez1

  • 1University of Bristol, Bristol BS8 1TH, UK.

Experimental biology and medicine (Maywood, N.J.)
|December 7, 2023
PubMed
概括

这项研究引入了一种新的类分解转移学习 (CDTL) 方法,用于使用结构性MRI扫描检测阿尔茨海默病 (AD). 该方法有效地解决了阶级不平衡,并在预测轻度认知障碍到AD转换方面取得了高准确性.

关键词:
阿尔茨海默氏症是阿尔茨海默氏症的一种疾病.结构性核磁共振成像 (MRI)类分解类的分解轻度的认知障碍 轻度的认知障碍转移学习转移学习

更多相关视频

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451
05:17

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451

Published on: April 18, 2025

177
Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

16.9K

相关实验视频

Last Updated: Jul 9, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.1K
Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451
05:17

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451

Published on: April 18, 2025

177
Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

16.9K

科学领域:

  • 神经成像是一种神经成像.
  • 人工智能的人工智能
  • 医学诊断 医学诊断 医学诊断

背景情况:

  • 使用结构磁共振成像 (sMRI) 进行阿尔茨海默病 (AD) 的计算机辅助诊断正在取得进展.
  • 从头开始训练像卷积神经网络这样的深度学习模型受到广泛的数据和计算要求的阻碍.
  • 数据集中的类失衡可能导致机器学习模型的预测性能差.

研究的目的:

  • 提出和评估一种类分解转移学习 (CDTL) 方法,用于从sMRI检测AD.
  • 评估CDTL方法在各种阿尔茨海默病神经成像计划 (ADNI) 队伍中的稳定性.
  • 为了改善轻度认知障碍 (MCI) 到AD转换的预测.

主要方法:

  • 员工通过利用预先培训的模型 (VGG19,AlexNet) 转移学习.
  • 使用类分解技术来处理数据集的不规则性和类不平衡.
  • 集成了一种基于的方法,用于增强分类.

主要成果:

  • CDTL方法在从sMRI数据中检测AD方面表现出有效性.
  • 在不同的ADNI队伍中观察到可比的分类准确性,表明了强度.
  • 在预测MCI转换为AD的准确度达到91.45%的最先进性能.

结论:

  • 拟议的CDTL方法为sMRI的AD检测提供了一个实用和有效的解决方案.
  • 转移学习和类分解是克服医学图像分析挑战的有价值的策略.
  • 该模型显示了早期检测和预测AD进展的巨大潜力.