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Recent advancements in medicine have confirmed that brain disorders often comprise multiple subtypes of mechanisms, developmental trajectories, or severity levels. Such heterogeneity is often associated with demographic aspects (e.g., sex)…

图像与视频处理 · 电气工程与系统科学 2024-10-08 Magdalini Paschali , Yu Hang Jiang , Spencer Siegel , Camila Gonzalez , Kilian M. Pohl , Akshay Chaudhari , Qingyu Zhao

Background: Huntington's disease (HD) is a rare, genetically determined brain disorder that limits the life of the patient, although early prognosis of HD can substantially improve the patient's quality of life. Current HD prognosis methods…

信号处理 · 电气工程与系统科学 2023-02-09 Sucheer Maddury

When evaluating the efficacy of social programs and medical treatments using randomized experiments, the estimated overall average causal effect alone is often of limited value and the researchers must investigate when the treatments do and…

应用统计 · 统计学 2013-05-27 Kosuke Imai , Marc Ratkovic

It is of great interest to quantify the contributions of genetic variation to brain structure and function, which are usually measured by high-dimensional imaging data (e.g., magnetic resonance imaging). In addition to the variance, the…

应用统计 · 统计学 2020-05-05 Benjamin B. Risk , Hongtu Zhu

Motivated by applications in neuroanatomy, we propose a novel methodology for estimating the heritability which corresponds to the proportion of phenotypic variance which can be explained by genetic factors. Estimating this quantity for…

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder characterized by motor dysfunction, psychiatric disturbances, and cognitive decline. The onset of HD is marked by severe motor impairment, which may be predicted…

统计方法学 · 统计学 2026-02-17 Yue Zhan , Cheng Zheng , Ying Zhang

In this paper, we focus on how to locate the relevant or discriminative brain regions related with external stimulus or certain mental decease, which is also called support identification, based on the neuroimaging data. The main difficulty…

计算机视觉与模式识别 · 计算机科学 2015-06-09 Yilun Wang , Sheng Zhang , Junjie Zheng , Heng Chen , Huafu Chen

Brain aging is a regional phenomenon, a facet that remains relatively under-explored within the realm of brain age prediction research using machine learning methods. Voxel-level predictions can provide localized brain age estimates that…

计算机视觉与模式识别 · 计算机科学 2024-04-26 Neha Gianchandani , Mahsa Dibaji , Johanna Ospel , Fernando Vega , Mariana Bento , M. Ethan MacDonald , Roberto Souza

Brain segmentation at different levels is generally represented as hierarchical trees. Brain regional atrophy at specific levels was found to be marginally associated with Alzheimer's disease outcomes. In this study, we propose an L1-type…

应用统计 · 统计学 2021-04-02 Yi Zhao , Bingkai Wang , Chin-Fu Liu , Andreia V. Faria , Michael I. Miller , Brian S. Caffo , Xi Luo

Functional brain connectivity, as revealed through distant correlations in the signals measured by functional Magnetic Resonance Imaging (fMRI), is a promising source of biomarkers of brain pathologies. However, establishing and using…

Understanding individual differences in cortical structure is key to advancing diagnostics in neurology and psychiatry. Reference models aid in detecting aberrant cortical thickness, yet site-specific biases limit their direct application…

计算机视觉与模式识别 · 计算机科学 2025-09-24 Christian Wachinger , Dennis Hedderich , Melissa Thalhammer , Fabian Bongratz

All neuroimaging modalities have their own strengths and limitations. A current trend is toward interdisciplinary approaches that use multiple imaging methods to overcome limitations of each method in isolation. At the same time…

统计方法学 · 统计学 2023-03-30 Pratim Guha Niyogi , Martin A. Lindquist , Tapabrata Maiti

Instrumental variable methods have been widely used to identify causal effects in the presence of unmeasured confounding. A key identification condition known as the exclusion restriction states that the instrument cannot have a direct…

统计方法学 · 统计学 2022-08-05 Baoluo Sun , Yifan Cui , Eric Tchetgen Tchetgen

In the high-dimensional landscape, addressing the challenges of covariance regression with high-dimensional covariates has posed difficulties for conventional methodologies. This paper addresses these hurdles by presenting a novel approach…

统计方法学 · 统计学 2024-04-11 Yuheng He , Changliang Zou , Yi Zhao

Neurodegenerative diseases are frequently associated with structural changes in the brain. Magnetic Resonance Imaging (MRI) scans can show these variations and therefore be used as a supportive feature for a number of neurodegenerative…

The improvements in magnetic resonance imaging have led to the development of numerous techniques to better detect structural alterations caused by neurodegenerative diseases. Among these, the patch-based grading framework has been proposed…

图像与视频处理 · 电气工程与系统科学 2020-01-24 Kilian Hett , Hans Johnson , Pierrick Coupé , Jane Paulsen , Jeffrey Long , Ipek Oguz

Longitudinal magnetic resonance imaging data is used to model trajectories of change in brain regions of interest to identify areas susceptible to atrophy in those with neurodegenerative conditions like Alzheimer's disease. Most methods for…

应用统计 · 统计学 2024-07-25 Robert Zielinski , Kun Meng , Ani Eloyan

Huntington disease (HD) is a neurodegenerative disease with progressively worsening symptoms. Accurately modeling time to HD diagnosis is essential for clinical trial design. Langbehn's model, the CAG-Age Product (CAP) model, the Prognostic…

There is an increasing interest in estimating heterogeneity in causal effects in randomized and observational studies. However, little research has been conducted to understand heterogeneity in an instrumental variables study. In this work,…

统计方法学 · 统计学 2021-01-20 Michael Johnson , Jiongyi Cao , Hyunseung Kang

In this paper, we develop an analytical approach for estimating brain connectivity networks that accounts for subject heterogeneity. More specifically, we consider a novel extension of a multi-subject Bayesian vector autoregressive model…

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