咨询与建议

限定检索结果

文献类型

  • 488 篇 期刊文献
  • 166 篇 会议

馆藏范围

  • 654 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 265 篇 医学
    • 216 篇 临床医学
    • 98 篇 基础医学(可授医学...
    • 42 篇 公共卫生与预防医...
    • 29 篇 药学(可授医学、理...
    • 15 篇 特种医学
    • 6 篇 中西医结合
    • 6 篇 医学技术(可授医学...
  • 181 篇 理学
    • 108 篇 生物学
    • 27 篇 数学
    • 21 篇 物理学
    • 15 篇 统计学(可授理学、...
    • 12 篇 化学
  • 169 篇 工学
    • 68 篇 生物医学工程(可授...
    • 63 篇 计算机科学与技术...
    • 62 篇 软件工程
    • 45 篇 光学工程
    • 39 篇 生物工程
    • 12 篇 信息与通信工程
    • 11 篇 电气工程
    • 10 篇 电子科学与技术(可...
    • 9 篇 化学工程与技术
    • 8 篇 控制科学与工程
    • 6 篇 仪器科学与技术
    • 5 篇 建筑学
    • 5 篇 土木工程
  • 30 篇 管理学
    • 13 篇 公共管理
    • 10 篇 图书情报与档案管...
    • 7 篇 管理科学与工程(可...
  • 26 篇 农学
    • 5 篇 作物学
  • 17 篇 教育学
    • 14 篇 心理学(可授教育学...
  • 3 篇 法学
  • 3 篇 文学

主题

  • 48 篇 functional magne...
  • 32 篇 neuroimaging
  • 30 篇 brain modeling
  • 21 篇 magnetic resonan...
  • 20 篇 biomedical imagi...
  • 19 篇 deep learning
  • 19 篇 independent comp...
  • 17 篇 correlation
  • 16 篇 feature extracti...
  • 15 篇 schizophrenia
  • 14 篇 engineering in m...
  • 13 篇 predictive model...
  • 13 篇 visualization
  • 13 篇 data models
  • 12 篇 biomarkers
  • 12 篇 electroencephalo...
  • 11 篇 depression
  • 11 篇 signal processin...
  • 11 篇 biological syste...
  • 11 篇 accuracy

机构

  • 22 篇 tri-institutiona...
  • 19 篇 tri-institutiona...
  • 11 篇 department of me...
  • 10 篇 department of in...
  • 10 篇 georgia state un...
  • 9 篇 tri-institutiona...
  • 8 篇 department of tw...
  • 8 篇 university of gl...
  • 8 篇 department of co...
  • 7 篇 national institu...
  • 7 篇 stanley center f...
  • 7 篇 university of pi...
  • 7 篇 institute for ca...
  • 7 篇 imim barcelona
  • 7 篇 wellcome centre ...
  • 7 篇 center for genom...
  • 7 篇 emory university...
  • 7 篇 tri-institutiona...
  • 7 篇 tri-institutiona...
  • 7 篇 harvard medical ...

作者

  • 89 篇 vince d. calhoun
  • 31 篇 armin iraji
  • 22 篇 vince d calhoun
  • 22 篇 calhoun vince d.
  • 21 篇 vince calhoun
  • 17 篇 zening fu
  • 16 篇 robyn l. miller
  • 14 篇 jingyu liu
  • 12 篇 anees abrol
  • 10 篇 tülay adali
  • 10 篇 charles a. ellis
  • 9 篇 kari stefansson
  • 9 篇 jing sui
  • 8 篇 bakas spyridon
  • 8 篇 caroline hayward
  • 8 篇 shile qi
  • 8 篇 rongtao jiang
  • 7 篇 timothy m frayli...
  • 7 篇 mark i mccarthy
  • 7 篇 henrik zetterber...

语言

  • 636 篇 英文
  • 12 篇 其他
  • 6 篇 中文
检索条件"机构=Center for Translational Research in Neuroimaging and Data Science"
654 条 记 录,以下是1-10 订阅
排序:
Beyond Artifacts: Rethinking Motion-Related Signals in Resting-State fMRI Analysis  46
Beyond Artifacts: Rethinking Motion-Related Signals in Resti...
收藏 引用
46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024
作者: Kumar, Samujjwal Kinsey, Spencer Jensen, Kyle M. Bajracharya, Prerana Calhoun, Vince D. Iraji, Armin Tri-Institutional Center for Translational Research in Neuroimaging and Data Science United States Georgia State University United States
Resting-state functional magnetic resonance imaging (rsfMRI) plays a pivotal role in estimating intrinsic brain functional connectivity within healthy and clinical populations. However, the pervasive impact of head mo... 详细信息
来源: 评论
MART(Splitting-Merging Assisted Reliable)Independent Component Analysis for Extracting Accurate Brain Functional Networks
收藏 引用
Neuroscience Bulletin 2024年 第7期40卷 905-920页
作者: Xingyu He Vince D.Calhoun Yuhui Du School of Computer and Information Technology Shanxi UniversityTaiyuan 030006China Tri-Institutional Center for Translational Research in Neuroimaging and Data Science Georgia State UniversityGeorgia Institute of TechnologyEmory UniversityAtlanta 30303USA
Functional networks(FNs)hold significant promise in understanding brain *** component analysis(ICA)has been applied in estimating FNs from functional magnetic resonance imaging(fMRI).However,determining an optimal mod... 详细信息
来源: 评论
Functionally-Adaptive Gray and White Matter Structural Basis Sets via Dynamic Fusion of Multimodal MRI data  46
Functionally-Adaptive Gray and White Matter Structural Basis...
收藏 引用
46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024
作者: Duda, Marlena Calhoun, Vince D. Georgia State University Georgia Tech Emory University Center for Translational Research in Neuroimaging and Data Science AtlantaGA United States
The exact nature of the coupling of brain structure and function has long been an open area of research. Often, this question is approached by first defining a single structural basis set, and then estimating function... 详细信息
来源: 评论
Evaluating Augmentation Approaches for Deep Learning-based Major Depressive Disorder Diagnosis with Raw Electroencephalogram data  46
Evaluating Augmentation Approaches for Deep Learning-based M...
收藏 引用
46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024
作者: Ellis, Charles A. Miller, Robyn L. Calhoun, Vince D. Georgia State University Emory University Georgia Institute of Technology Center for Translational Research in Neuroimaging and Data Science Atlanta United States
While deep learning methods are increasingly applied in research contexts for neuropsychiatric disorder diagnosis, small dataset size limits their potential for clinical translation. data augmentation (DA) could addre... 详细信息
来源: 评论
Identifying Reproducibly Important EEG Markers of Schizophrenia with an Explainable Multi-Model Deep Learning Approach  46
Identifying Reproducibly Important EEG Markers of Schizophre...
收藏 引用
46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024
作者: Sancho, Martina Lapera Ellis, Charles A. Miller, Robyn L. Calhoun, Vince D. Georgia State University Georgia Institute of Technology Emory University Tri-Institutional Center for Translational Research in Neuroimaging and Data Science Atlanta United States
The diagnosis of schizophrenia (SZ) can be challenging due to its diverse symptom presentation. As such, many studies have sought to identify diagnostic biomarkers of SZ using explainable machine learning methods. How... 详细信息
来源: 评论
data augmentation for schizophrenia diagnosis via vision transformer-based latent diffusion model  4
Data augmentation for schizophrenia diagnosis via vision tra...
收藏 引用
4th International Conference on Biomedicine and Bioinformatics Engineering, ICBBE 2024
作者: Yang, Yuxuan Ma, Shidong Cao, Shengjie Jia, Sihan Bi, Yuda Calhoun, Vince D. Shandong University of Science and Technology Shandong Qingdao China Tri-institutional Center for Translational Research in Neuroimaging and Data Science GSU GATech Emory AtlantaGA30303 United States
Schizophrenia (SZ) is a complex and heterogeneous disorder. Characterizing functional magnetic resonance imaging (fMRI) imaging patterns specific to SZ is challenging and can benefit greatly from advanced artificial i... 详细信息
来源: 评论
Improving Multichannel Raw Electroencephalography-based Diagnosis of Major Depressive Disorder via Transfer Learning with Single Channel Sleep Stage data
Improving Multichannel Raw Electroencephalography-based Diag...
收藏 引用
2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023
作者: Ellis, Charles A. Sattiraju, Abhinav Miller, Robyn L. Calhoun, Vince D. Georgia State University Georgia Institute of Technology Emory University Tri-Institutional Center for Translational Research in Neuroimaging and Data Science Atlanta United States
As the field of deep learning has grown in recent years, its application to the domain of raw resting-state electroencephalography (EEG) has also increased. Relative to traditional machine learning methods or deep lea... 详细信息
来源: 评论
Improving Explainability for Single-Channel EEG Deep Learning Classifiers via Interpretable Filters and Activation Analysis
Improving Explainability for Single-Channel EEG Deep Learnin...
收藏 引用
2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023
作者: Ellis, Charles A. Miller, Robyn L. Calhoun, Vince D. Georgia State University Georgia Institute of Technology Emory University Tri-Institutional Center for Translational Research in Neuroimaging and Data Science Atlanta United States
Deep learning methods are increasingly being applied to raw electroencephalography (EEG) data. Relative to traditional machine learning methods, deep learning methods can increase model performance through automated f... 详细信息
来源: 评论
An Explainable and Robust Deep Learning Approach for Automated Electroencephalography-based Schizophrenia Diagnosis  23
An Explainable and Robust Deep Learning Approach for Automat...
收藏 引用
23rd IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2023
作者: Sattrraju, Abhmav Ellis, Charles A. Miller, Robyn L. Calhoun, Vince D. The Tri-institutional Center for Translational Research in Neuroimaging and Data Science Georgia State University Georgia Institute of Technology Emory University AtlantaGA30303 United States
Schizophrenia (SZ) is a neuropsychiatric disorder that affects millions globally. Current diagnosis of SZ is symptom-based, which poses difficulty due to the variability of symptoms across patients. To this end, many ... 详细信息
来源: 评论
Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs
Cross-Modal Synthesis of Structural MRI and Functional Conne...
收藏 引用
International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Yuda Bi Anees Abrol Jing Sui Vince Calhoun Tri-Institutional Center for Translational Research in Neuroimaging and Data Science @{GSU GATech Emory}
The cross-modal synthesis between structural magnetic resonance imaging (sMRI) and functional network connectivity (FNC) is a relatively unexplored area in medical imaging, especially with respect to schizophrenia. Th...
来源: 评论