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

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

Localized gold nanoparticles-mediated photothermal therapy for head and neck cancer: in vivo proof-of-concept.

International journal of pharmaceutics·2026
Same author

Cognitive performance in youth football players: Evidence from spectral and temporal EEG analyses.

Psychology of sport and exercise·2026
Same author

Real-World Generalizability of Alzheimer's Volumetric MRI Machine-Learning Models: External Validation with British Data.

Clinical neuroradiology·2026
Same author

Psychological and hormonal effects of socio-emotional learning in adolescents: a randomized controlled trial.

Humanities & social sciences communications·2025
Same author

Healthy Life Years After 65: Building on Portugal's Progress with Stronger Geriatric Medicine.

Acta medica portuguesa·2025
Same author

Fourier Transforms the way we see B-lines in Lung Ultrasound.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

相关实验视频

Updated: Jun 11, 2025

Detecting Amyloid-β Accumulation via Immunofluorescent Staining in a Mouse Model of Alzheimer's Disease
08:25

Detecting Amyloid-β Accumulation via Immunofluorescent Staining in a Mouse Model of Alzheimer's Disease

Published on: April 19, 2021

3.2K

使用形态学磁共振成像检测粉样蛋白阳性

Helena Rico Pereira1,2, Vasco Sá Diogo1,3, Diana Prata1,4,5

  • 1Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências da Universidade de Lisboa, Lisbon, Portugal.

Journal of Alzheimer's disease : JAD
|September 27, 2024
PubMed
概括

这项研究使用MRI扫描来检测粉样蛋白-β (Aβ) 对阿尔茨海默病 (AD) 诊断的阳性. 机器学习模型显示了使用脑成像和认知数据对Aβ状态进行分类的潜力.

关键词:
阿尔茨海默氏症是阿尔茨海默氏症的一种疾病.粉样化物-β-β 的存在.痴呆症 痴呆症是一种痴呆症.诊断成像诊断成像的使用.机器学习是机器学习.

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

115
Imaging Amyloid Tissues Stained with Luminescent Conjugated Oligothiophenes by Hyperspectral Confocal Microscopy and Fluorescence Lifetime Imaging
10:04

Imaging Amyloid Tissues Stained with Luminescent Conjugated Oligothiophenes by Hyperspectral Confocal Microscopy and Fluorescence Lifetime Imaging

Published on: October 20, 2017

13.4K

相关实验视频

Last Updated: Jun 11, 2025

Detecting Amyloid-β Accumulation via Immunofluorescent Staining in a Mouse Model of Alzheimer's Disease
08:25

Detecting Amyloid-β Accumulation via Immunofluorescent Staining in a Mouse Model of Alzheimer's Disease

Published on: April 19, 2021

3.2K
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

115
Imaging Amyloid Tissues Stained with Luminescent Conjugated Oligothiophenes by Hyperspectral Confocal Microscopy and Fluorescence Lifetime Imaging
10:04

Imaging Amyloid Tissues Stained with Luminescent Conjugated Oligothiophenes by Hyperspectral Confocal Microscopy and Fluorescence Lifetime Imaging

Published on: October 20, 2017

13.4K

科学领域:

  • 神经成像是一种神经成像.
  • 阿尔茨海默氏症疾病研究研究
  • 机器学习在医学中的应用

背景情况:

  • 早期发现粉样β (Aβ) 阳性对于阿尔茨海默病 (AD) 的诊断和治疗至关重要.
  • 目前用于Aβ检测的方法通常是昂贵的和侵入性的.

研究的目的:

  • 使用磁共振成像 (MRI) 形态特征来分类Aβ阳性.
  • 评估混合 (AD,MCI,CN) 和认知障碍 (AD,MCI) 人群中的分类性能.

主要方法:

  • 综合的人口,认知 (MMSE),区域MRI形态测量和图形理论 (GT) 的特征.
  • 利用机器学习工作流来开发Aβ+分类模型.
  • 分析了302名Aβ+和246名Aβ-受试者的数据.

主要成果:

  • 在AD+MCI+CN场景中,一个具有120个特征的模型 (107个GT,12个MRI,MMSE) 实现了66.9%的平衡精度.
  • 在AD+MCI场景中,一个具有180个MRI特征的模型实现了70.7%的平衡精度.
  • 这两种模型都表明了Aβ状态分类的潜力.

结论:

  • 区域MRI形态特征显示了非侵入性检测Aβ状态的潜力.
  • 将MRI特征与认知数据相结合可能会提高分类准确性,特别是在混合人群中.
  • 需要进一步的研究来提高临床适用性.