Machine Learning and Large-scale Imaging analytics for dimensional representations of brain trajectories in aging and preclinical Alzheimer's Disease: The brain aging chart and the iSTAGING consortium

机器学习和大规模成像分析,用于衰老和临床前阿尔茨海默氏病大脑轨迹的维度表示:大脑衰老图表和 iSTAGING 联盟

基本信息

  • 批准号:
    10839623
  • 负责人:
  • 金额:
    $ 24.38万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-04-15 至 2025-08-31
  • 项目状态:
    未结题

项目摘要

Abstract The parent grant has been building a truly unique database of MRI, clinical and cognitive data from over 65,000 individuals and 16 distinct studies. It has been constructing machine learning models and biomarkers aiming to capture the heterogeneity of brain aging and derive predictive models of cognitive decline. The current supplement will build the foundation for making these pipelines available very easily through cloud computing. More specifically, the focus of this supplement will be to build the infrastructure for a web-based portal running n the AWS cloud, which will allow for seamless “drag-and-drop” of MRIs for application of the pipelines developed by the parent program. This will facilitate the wide access of these pipelines without the need to set up local software and familiarize with complex preprocessing of MRI datasets and machine learning pipelines.
摘要 父母补助金一直在建立一个真正独特的MRI,临床和认知数据库, 65,000人和16项不同的研究。它一直在构建机器学习模型, 生物标志物,旨在捕捉大脑老化的异质性,并推导出认知功能的预测模型。 下降目前的补充将建立基础,使这些管道非常容易 通过云计算。更具体地说,这一补充的重点将是建设基础设施 用于在AWS云上运行的基于Web的门户,这将允许MRI的无缝“拖放” 用于应用由父程序开发的管道。这将有助于广泛获得 这些管道,而无需设置本地软件和熟悉复杂的预处理, MRI数据集和机器学习管道。

项目成果

期刊论文数量(26)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Subject-Specific Structural Parcellations Based on Randomized AB-divergences.
Embracing the disharmony in medical imaging: A Simple and effective framework for domain adaptation.
  • DOI:
    10.1016/j.media.2021.102309
  • 发表时间:
    2022-03
  • 期刊:
  • 影响因子:
    10.9
  • 作者:
    Wang R;Chaudhari P;Davatzikos C
  • 通讯作者:
    Davatzikos C
Longitudinally and inter-site consistent multi-atlas based parcellation of brain anatomy using harmonized atlases.
  • DOI:
    10.1016/j.neuroimage.2017.10.026
  • 发表时间:
    2018-02-01
  • 期刊:
  • 影响因子:
    5.7
  • 作者:
    Erus G;Doshi J;An Y;Verganelakis D;Resnick SM;Davatzikos C
  • 通讯作者:
    Davatzikos C
Modifiable vascular risk factors, white matter disease and cognition in early Parkinson's disease.
  • DOI:
    10.1111/ene.13797
  • 发表时间:
    2019-03
  • 期刊:
  • 影响因子:
    5.1
  • 作者:
    Chahine LM;Dos Santos C;Fullard M;Scordia C;Weintraub D;Erus G;Rosenthal L;Davatzikos C;McMillan CT
  • 通讯作者:
    McMillan CT
A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages.
  • DOI:
    10.1016/j.neuroimage.2017.03.057
  • 发表时间:
    2017-07-15
  • 期刊:
  • 影响因子:
    5.7
  • 作者:
    Rathore S;Habes M;Iftikhar MA;Shacklett A;Davatzikos C
  • 通讯作者:
    Davatzikos C
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Christos Davatzikos其他文献

Christos Davatzikos的其他文献

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{{ truncateString('Christos Davatzikos', 18)}}的其他基金

Disentangling the anatomical, functional and clinical heterogeneity of major depression, using machine learning methods
使用机器学习方法解开重度抑郁症的解剖学、功能和临床异质性
  • 批准号:
    10714834
  • 财政年份:
    2023
  • 资助金额:
    $ 24.38万
  • 项目类别:
The Neuroimaging Brain Chart Software Suite
神经影像脑图软件套件
  • 批准号:
    10581015
  • 财政年份:
    2023
  • 资助金额:
    $ 24.38万
  • 项目类别:
Generalizable quantitative imaging and machine learning signatures in glioblastoma, for precision diagnostics and personalized treatment: the ReSPOND consortium
胶质母细胞瘤的通用定量成像和机器学习特征,用于精确诊断和个性化治疗:ReSPOND 联盟
  • 批准号:
    10625442
  • 财政年份:
    2022
  • 资助金额:
    $ 24.38万
  • 项目类别:
Generalizable quantitative imaging and machine learning signatures in glioblastoma, for precision diagnostics and personalized treatment: the ReSPOND consortium
胶质母细胞瘤的通用定量成像和机器学习特征,用于精确诊断和个性化治疗:ReSPOND 联盟
  • 批准号:
    10421222
  • 财政年份:
    2022
  • 资助金额:
    $ 24.38万
  • 项目类别:
Ultrascale Machine Learning to Empower Discovery in Alzheimers Disease Biobanks
超大规模机器学习助力阿尔茨海默病生物库的发现
  • 批准号:
    10696100
  • 财政年份:
    2020
  • 资助金额:
    $ 24.38万
  • 项目类别:
Ultrascale Machine Learning to Empower Discovery in Alzheimers Disease Biobanks
超大规模机器学习助力阿尔茨海默病生物库的发现
  • 批准号:
    10263220
  • 财政年份:
    2020
  • 资助金额:
    $ 24.38万
  • 项目类别:
Benchmarking and Comparing AD-Related AI Methods Across Sites on a Standardized Dataset
在标准化数据集上跨站点对 AD 相关 AI 方法进行基准测试和比较
  • 批准号:
    10825403
  • 财政年份:
    2020
  • 资助金额:
    $ 24.38万
  • 项目类别:
Ultrascale Machine Learning to Empower Discovery in Alzheimers Disease Biobanks
超大规模机器学习助力阿尔茨海默病生物库的发现
  • 批准号:
    10475286
  • 财政年份:
    2020
  • 资助金额:
    $ 24.38万
  • 项目类别:
Ultrascale Machine Learning to Empower Discovery in Alzheimers Disease Biobanks
超大规模机器学习助力阿尔茨海默病生物库的发现
  • 批准号:
    10028746
  • 财政年份:
    2020
  • 资助金额:
    $ 24.38万
  • 项目类别:
Biomedical Image Computing and Informatics Cluster
生物医学图像计算与信息学集群
  • 批准号:
    9273767
  • 财政年份:
    2017
  • 资助金额:
    $ 24.38万
  • 项目类别:

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