Christos Davatzikos
Biographic Data
| ID | 4467565 |
|---|---|
| NAME | Christos Davatzikos |
| GIVEN NAMES | Christos |
| FAMILY NAME | Davatzikos |
| SIGNATURE | DAVATZIKOS C |
| AFFILIATIONS | University of Pennsylvania |
| ORCID | 0000-0002-1025-8561 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Development of Simple Risk Scores for Prediction of Brain β-Amyloid and Tau Status in Older Adults With Mild Cognitive Impairment
Objectives The aim of this work is to use a machine learning framework to develop simple risk scores for predicting β-amyloid (Aβ) and tau positivity among individuals with mild cognitive impairment (MCI). Methods Data for 657 individuals with MCI from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data set were used. A modified version of AutoScore, a machine learning-based software tool, was used to develop risk scores based on hierarch…
The Role of Race in Relations of Social Support to Hippocampal Volumes Among Older Adults
Evidence suggests social support may buffer brain pathology. However, neither its association with hippocampal volume, a marker of Alzheimer’s disease risk, nor the role of race in this association has been fully investigated. Multiple regression analyses examined relations of total social support to magnetic resonance imaging-assessed gray matter (GM) hippocampal volumes in the total sample ( n = 165; mean age = 68.48 year), and in race-stratifi…
Commentary to “Translational machine learning for child and adolescent psychiatry”
In this commentary on ‘Translational Machine Learning for Child and Adolescent Psychiatry,’ by Dwyer and Koutsouleris, we summarize some of the main points made by the authors, which highlight the importance of emerging applications of machine learning for psychiatric disorders in youth but also emphasize principles of good practice. We also offer complementary insights regarding large‐scale training, harmonization, and the ability of these artif…
Differential Associations of Socioeconomic Status With Global Brain Volumes and White Matter Lesions in African American and White Adults
OBJECTIVE: The aim of the study was to examine interactive relations of race and socioeconomic status (SES) to magnetic resonance imaging (MRI)-assessed global brain outcomes with previously demonstrated prognostic significance for stroke, dementia, and mortality. METHODS: Participants were 147 African Americans (AAs) and whites (ages 33-71 years; 43% AA; 56% female; 26% below poverty) in the Healthy Aging in Neighborhoods of Diversity across the…
Development of Simple Risk Scores for Prediction of Brain β-Amyloid and Tau Status in Older Adults With Mild Cognitive Impairment
Objectives The aim of this work is to use a machine learning framework to develop simple risk scores for predicting β-amyloid (Aβ) and tau positivity among individuals with mild cognitive impairment (MCI). Methods Data for 657 individuals with MCI from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data set were used. A modified version of AutoScore, a machine learning-based software tool, was used to develop risk scores based on hierarch…
Differential Associations of Socioeconomic Status With Global Brain Volumes and White Matter Lesions in African American and White Adults
OBJECTIVE: The aim of the study was to examine interactive relations of race and socioeconomic status (SES) to magnetic resonance imaging (MRI)-assessed global brain outcomes with previously demonstrated prognostic significance for stroke, dementia, and mortality. METHODS: Participants were 147 African Americans (AAs) and whites (ages 33-71 years; 43% AA; 56% female; 26% below poverty) in the Healthy Aging in Neighborhoods of Diversity across the…
The Role of Race in Relations of Social Support to Hippocampal Volumes Among Older Adults
Evidence suggests social support may buffer brain pathology. However, neither its association with hippocampal volume, a marker of Alzheimer’s disease risk, nor the role of race in this association has been fully investigated. Multiple regression analyses examined relations of total social support to magnetic resonance imaging-assessed gray matter (GM) hippocampal volumes in the total sample ( n = 165; mean age = 68.48 year), and in race-stratifi…
Commentary to “Translational machine learning for child and adolescent psychiatry”
In this commentary on ‘Translational Machine Learning for Child and Adolescent Psychiatry,’ by Dwyer and Koutsouleris, we summarize some of the main points made by the authors, which highlight the importance of emerging applications of machine learning for psychiatric disorders in youth but also emphasize principles of good practice. We also offer complementary insights regarding large‐scale training, harmonization, and the ability of these artif…
Development of Simple Risk Scores for Prediction of Brain β-Amyloid and Tau Status in Older Adults With Mild Cognitive Impairment
Objectives The aim of this work is to use a machine learning framework to develop simple risk scores for predicting β-amyloid (Aβ) and tau positivity among individuals with mild cognitive impairment (MCI). Methods Data for 657 individuals with MCI from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data set were used. A modified version of AutoScore, a machine learning-based software tool, was used to develop risk scores based on hierarch…
Dementia and Cognitive Impairment Research (3 works) · Psychology (3 works) · Developmental psychology (2 works) · Magnetic resonance imaging (2 works) · Medicine (2 works) · Neuroscience (2 works) · White matter (2 works) · Acute Ischemic Stroke Management (1 works) · African american (1 works) · Alzheimer's disease research and treatments (1 works)