Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG013743-02
Application #
2055736
Study Section
Special Emphasis Panel (SRCM (01))
Project Start
1995-09-30
Project End
1998-06-30
Budget Start
1996-09-01
Budget End
1997-06-30
Support Year
2
Fiscal Year
1996
Total Cost
Indirect Cost
Name
Johns Hopkins University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
045911138
City
Baltimore
State
MD
Country
United States
Zip Code
21218
Chen, Rong; Krejza, Jaroslaw; Arkuszewski, Michal et al. (2017) Brain morphometric analysis predicts decline of intelligence quotient in children with sickle cell disease: A preliminary study. Adv Med Sci 62:151-157
Chen, Rong; Herskovits, Edward H (2015) Examining the multifactorial nature of a cognitive process using Bayesian brain-behavior modeling. Comput Med Imaging Graph 41:117-25
Chen, Rong; Herskovits, Edward H (2012) Graphical model based multivariate analysis (GAMMA): an open-source, cross-platform neuroimaging data analysis software package. Neuroinformatics 10:119-27
Jiao, Yun; Chen, Rong; Ke, Xiaoyan et al. (2012) Single nucleotide polymorphisms predict symptom severity of autism spectrum disorder. J Autism Dev Disord 42:971-83
Chen, Rong; Resnick, Susan M; Davatzikos, Christos et al. (2012) Dynamic Bayesian network modeling for longitudinal brain morphometry. Neuroimage 59:2330-8
Chen, Rong; Jiao, Yun; Herskovits, Edward H (2011) Structural MRI in autism spectrum disorder. Pediatr Res 69:63R-8R
Jiao, Y; Chen, R; Ke, X et al. (2011) Predictive models for subtypes of autism spectrum disorder based on single-nucleotide polymorphisms and magnetic resonance imaging. Adv Med Sci 56:334-42
Chen, Rong; Herskovits, Edward H (2010) Voxel-based Bayesian lesion-symptom mapping. Neuroimage 49:597-602
Jiao, Yun; Chen, Rong; Ke, Xiaoyan et al. (2010) Predictive models of autism spectrum disorder based on brain regional cortical thickness. Neuroimage 50:589-99
Chen, Rong; Herskovits, Edward H (2010) Machine-learning techniques for building a diagnostic model for very mild dementia. Neuroimage 52:234-44

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