ArticleHuman brain mapping2016
Extracting patterns of morphometry distinguishing HIV associated neurodegeneration from mild cognitive impairment via group cardinality constrained classification.
Article in Human brain mapping, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Applications of Machine Learning for Cognitive Health in Older Individuals With HIV: Rapid Systematic Review.JMIR aging · 2025Pooled it
- The prefrontal cortex, but not the medial temporal lobe, is associated with episodic memory in middle-aged persons with HIV.Journal of the International Neuropsychological Society : JINS · 2024Article
- The association of microbial infection and adaptive immune cell activation in Alzheimer's disease.Discovery immunology · 2023Review
- A Penalty Approach for Normalizing Feature Distributions to Build Confounder-Free Models.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2022Article
- Prior test experience confounds longitudinal tracking of adolescent cognitive and motor development.BMC medical research methodology · 2022Article
- Multi-label, multi-domain learning identifies compounding effects of HIV and cognitive impairment.Medical image analysis · 2022Article
- Alzheimer Disease and HIV: Untangling the Gordian Knot.Neurology. Clinical practice · 2021Article
- Cerebrovascular Disease Correlates With Longitudinal Brain Atrophy in Virally Suppressed Older People Living With HIV.Journal of acquired immune deficiency syndromes (1999) · 2021Article
- Metadata Normalization.Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition · 2021Article
- Logistic Regression Confined by Cardinality-Constrained Sample and Feature Selection.IEEE transactions on pattern analysis and machine intelligence · 2020Article
- Machine-learning classification of neurocognitive performance in children with perinatal HIV initiating de novo antiretroviral therapy.AIDS (London, England) · 2020Article
- Detecting cognitive impairment in HIV-infected individuals using mutual connectivity analysis of resting state functional MRI.Journal of neurovirology · 2020Article
- Longitudinal brain atrophy patterns and neuropsychological performance in older adults with HIV-associated neurocognitive disorder compared with early Alzheimer's disease.Neurobiology of aging · 2019Article
- The current understanding of overlap between characteristics of HIV-associated neurocognitive disorders and Alzheimer's disease.Journal of neurovirology · 2019Review
- Novel Machine Learning Identifies Brain Patterns Distinguishing Diagnostic Membership of Human Immunodeficiency Virus, Alcoholism, and Their Comorbidity of Individuals.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2019Article
- Article
- Multivariate Pattern Analysis of Volumetric Neuroimaging Data and Its Relationship With Cognitive Function in Treated HIV Disease.Journal of acquired immune deficiency syndromes (1999) · 2018Article
- Alcohol use effects on adolescent brain development revealed by simultaneously removing confounding factors, identifying morphometric patterns, and classifying individuals.Scientific reports · 2018Article
- A tale of two diseases: Aging HIV patients inspire a closer look at Alzheimer's disease.Nature medicine · 2018Article
- Differentiating HIV-Associated Neurocognitive Disorders From Alzheimer's Disease: an Emerging Issue in Geriatric NeuroHIV.Current HIV/AIDS reports · 2017Review
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
HIV-Associated Neurocognitive Disorder (HAND) is the most common constellation of cognitive dysfunctions in chronic HIV infected patients age 60 or older in the U.S. Only few published methods assist in distinguishing HAND from other forms of age-associated cognitive decline, such as Mild Cognitive Impairment (MCI). In this report, a data-driven, nonparameteric model to identify morphometric patterns separating HAND from MCI due to non-HIV conditions in this older age group was proposed. This model enhanced the potential for group separation by combining a smaller, longitudinal data set containing HAND samples with a larger, public data set including MCI cases. Using cross-validation, a linear model on healthy controls to harmonize the volumetric scores extracted from MRIs for demographic and acquisition differences between the two independent, disease-specific data sets was trained. Next, patterns distinguishing HAND from MCI via a group sparsity constrained logistic classifier were identified. Unlike existing approaches, our classifier directly solved the underlying minimization problem by decoupling the minimization of the logistic regression function from enforcing the group sparsity constraint. The extracted patterns consisted of eight regions that distinguished HAND from MCI on a significant level while being indifferent to differences in demographics and acquisition between the two sets. Individually selecting regions through conventional morphometric group analysis resulted in a larger number of regions that were less accurate. In conclusion, simultaneously analyzing all brain regions and time points for disease specific patterns contributed to distinguishing with high accuracy HAND-related impairment from cognitive impairment found in the HIV uninfected, MCI cohort. Hum Brain Mapp 37:4523-4538, 2016. © 2016 Wiley Periodicals, Inc.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.