Deanna Greenstein
Biographic Data
| ID | 7963515 |
|---|---|
| NAME | Deanna Greenstein |
| GIVEN NAMES | Deanna |
| FAMILY NAME | Greenstein |
| SIGNATURE | GREENSTEIN D |
| AFFILIATIONS | Child Psychiatry Branch, National Institutes of Mental Health, National Institutes of Health, Bethesda, MD 20892; and Laboratory of Neuro Imaging, Department of Neurology, University of California School of Medicine, Los Angeles, CA 90095-1769 |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2004 |
| LATEST PUBLICATION YEAR | 2012 |
| H-INDEX | 0 |
Using Multivariate Machine Learning Methods and Structural MRI to Classify Childhood Onset Schizophrenia and Healthy Controls
Schizophrenia and control groups can be well classified using RF and anatomic brain measures, and brain-based probability of illness has a positive relationship with illness severity and a negative relationship with developmental delays/problems and CNV-based risk
Dynamic mapping of human cortical development during childhood through early adulthood
We report the dynamic anatomical sequence of human cortical gray matter development between the age of 4–21 years using quantitative four-dimensional maps and time-lapse sequences. Thirteen healthy children for whom anatomic brain MRI scans were obtained every 2 years, for 8–10 years, were studied. By using models of the cortical surface and sulcal landmarks and a statistical model for gray matter density, human cortical development could be visu…
No prominent works on this page.
Dynamic mapping of human cortical development during childhood through early adulthood
We report the dynamic anatomical sequence of human cortical gray matter development between the age of 4–21 years using quantitative four-dimensional maps and time-lapse sequences. Thirteen healthy children for whom anatomic brain MRI scans were obtained every 2 years, for 8–10 years, were studied. By using models of the cortical surface and sulcal landmarks and a statistical model for gray matter density, human cortical development could be visu…
Using Multivariate Machine Learning Methods and Structural MRI to Classify Childhood Onset Schizophrenia and Healthy Controls
Schizophrenia and control groups can be well classified using RF and anatomic brain measures, and brain-based probability of illness has a positive relationship with illness severity and a negative relationship with developmental delays/problems and CNV-based risk
Advanced Neuroimaging Techniques and Applications (2 works) · Functional Brain Connectivity Studies (2 works) · Medicine (2 works) · Psychology (2 works) · Audiology (1 works) · Autism (1 works) · Biology (1 works) · Brain development (1 works) · Cerebral cortex (1 works) · Computer Science (1 works)